Market Returns and Mutual Fund Flows

Eli M. Remolona, Paul Kleiman, and Debbie Gruenstein

FRBNY ECONOMIC POLICY REVIEW / JULY 1997 33
Federal Reserve Bank of New York

The 1990s have seen unprecedented growth in mutual funds. Shares in the funds now represent a major part of household wealth, and the funds themselves have become important intermediaries for savings and investments. In the United States, more than 4,000 mutual funds cur-rently hold stocks and bonds worth a total of more than $2 trillion.

Household investment in these funds increased more than fivefold in the last ten years, making it the fastest growing item on the household financial balance sheet. Most of this growth came at the expense of more traditional forms of savings, particularly bank deposits. With the increased popularity of mutual funds come increased concerns—namely, could a sharp drop in stock or bond prices set off a cascade of redemptions by fund investors and could the redemptions exert further downward pressure on asset markets?

In recent years, flows into funds have generally been highly correlated with market returns. That is, mutual fund inflows have tended to accompany market upturns and out-flows have tended to accompany downturns. This cor-relation raises the question whether a positive-feedback process is at work here, in which market returns cause the flows at the same time that the flows cause the returns. Observers such as Hale (1994) and Kaufman (1994) fear that such a process could turn a decline in the stock or bond market into a downward spiral in asset prices.

In this study, we use recent historical evidence to explore one dimension of the broad relationship between market returns and mutual fund flows: the effect of short-term market returns on mutual fund flows. Research on this issue has already confirmed high correlations between market returns and aggregate mutual fund flows (Warther1995). A positive-feedback process, however, requires not just correlation but two-way causation between flows and returns, in which fund investors react to market move-ments while the market itself moves in response to the investors’ behavior.

Previous studies of causation have focused on the effects of past performance on flows into individual mutual funds, typically with a one-year lag separating cause and effect. In this article, however, we examine the effect of market-wide returns on aggregate mutual fund flows within a month, a level of aggregation and a time horizon that seem more consistent with the dynamics of a downward spiral in asset prices.

Our statistical analysis uses instrumental variables, a technique that is partic-ularly well suited for measuring causation when observed variables are likely to be determined simulta-neously. The technique has not been applied before to mutual fund flows and market returns.

Despite market observers’ fears of a downward spiral, our study suggests that the short-term effect of market returns on mutual fund flows typically has been too weak to sustain a spiral. During unusually severe market declines, stock and bond movements have prompted proportionately greater outflows than under normal conditions, but even at these times, the effect has not seemed strong enough to perpetuate a sharp fall in asset prices.

We begin by describing the nature of mutual funds and characterizing their recent growth. Next, we examine the data on aggregate mutual fund flows by dividing them into expected and unexpected components and investigating their correlations with market returns. The effects of returns on flows are then estimated using instrumental variables. Finally, we test the robustness of our estimates by looking at the flows during severe market declines.

THE NATURE AND GROWTH OF MUTUAL FUNDS

Mutual funds operate as tax-exempt financial institutions that pool resources from numerous shareholders to invest in a diversified portfolio of securities. Unlike closed-end funds, which issue a fixed number of shares, open-end mutual funds are obligated to redeem shares at the request of the shareholder. When a shareholder redeems shares, he or she receives their net asset value, which equals the value of the fund’s net assets divided by the number of shares outstanding. An investment manager determines the composition of the fund’s investment portfolio in accordance with the fund’s return objectives and risk criteria.

INVESTMENT OBJECTIVES AND FEE STRUCTURES

Mutual funds vary widely in their investment objectives. The Investment Company Institute (ICI)—the industry trade group whose membership includes almost all registered U.S. mutual funds—classifies mutual funds according to twenty-one investment objectives. For instance, some funds aim to provide a steady stream of income while others emphasize capital appreciation; some funds specialize in U.S. common stocks while others specialize in U.S. bonds or in foreign stocks and bonds.

It is important to gauge a fund’s performance relative to its investment objective because the different objectives repre-sent trade-offs between risk and return. Some objectives aim for high returns at high risk, others for more modest returns but at less risk.

Mutual funds also differ in their fee structures, which can affect the sensitivity of flows to a fund’s short-term performance. Many mutual funds charge an up-front sales fee, called a load, that is typically around 5 percent of the initial investment. The desire to spread the cost of the load over time may make a shareholder reluctant to sell in the short run. For example, Ippolito (1992) finds that poor performance leads to half as many withdrawals from load funds as from no-load funds. Chordia (1996) also provides evidence that such fees discourage redemptions. At the end of 1995, 62 percent of the assets in stock mutual funds and 66 percent of the assets in bond mutual funds were in load funds. Although no-load funds impose no up-front fees, many collect back-end fees, called contingent deferred sales charges, when shares are redeemed. These fees generally decline the longer the shares are held and thus also discourage investors from selling in the short run.

THE GROWTH OF MUTUAL FUNDS

Although mutual funds have existed in the United States since 1924, truly significant amounts of money did not start flowing into the funds until the mid-1980s. A decline in deposit rates in the early 1990s marked the beginning of explosive growth in the funds. As a result, mutual funds as a group have become important financial intermediaries and repositories of household wealth.

Households in 1995 held 10 percent of their net financial wealth in mutual fund shares directly and 3 percent indirectly through pension funds. At the end of 1995, the net assets of mutual funds were 60 percent as large as the assets held by commercial banks, a leap from only 27 percent at year-end 1986. Such rapid growth has prompted Hale (1994) to suggest that the rise of mutual funds is creating a whole new financial system.

Much of the growth in mutual funds can be attributed to the influx of retirement money driven by long-term demographic forces. Morgan (1994) shows that changes in the share of household assets held in stocks and bonds are explained by the proportion of workers thirty-five years of age or older. Workers reaching thirty-five years of age tend to earn enough to start saving for retire-ment, and mutual fund shares represent a way to invest their savings. Households also save through retirement plans, life insurance policies, and trust accounts with banks. Among these investments, retirement plans have been acquiring mutual fund shares at the highest rate: the share of mutual fund assets held by retirement plans expanded from 6.2 percent in 1986 to 16.4 per-centin 1995.

Life-cycle motives for investing in mutual funds—such as saving for retirement—can make certain flows insensitive to short-term returns, and much of these flows would be predictable on the basis of past flows. Hence, this analysis will distin-guish between long-term trends and short-term fluctu-ations in mutual fund flows.

As large as the recent flows have been, mutual funds still hold relatively small shares of the markets in which they invest. At the end of 1995, they held 16 percent of the capitalization of the municipal bond market, 12 percent of the corporate equity market, 7 percent of the corporate and foreign bond market, and 5 percent of the U.S.

Treasury and agency securities market. These fairly small shares limit the potential impact of the flows on asset prices. Estimates by Shleifer (1986) sug-gest that an exogenous decline in mutual funds’demand for stocks by one dollar would reduce the value of the market by one dollar. Such estimates imply that selling pressure by mutual funds alone is unlikely to cause a sharp market decline.

THE CORRELATION BETWEEN RETURNS AND FLOWS

The recent movements of large mutual fund flows suggest a strong correlation between market returns and the flows. In the early 1990s, the flows into stock and bond mutual funds were equally strong. However, when the Federal Reserve started to raise its target federal funds rate in February 1994, the bond market became bearish and the flows shifted sharply from bond to stock funds. More recently, the equity bull market in 1995 was accompanied by record flows into stock funds.

Such correlations between aggregate fund flows and marketwide returns suggest a positive-feedback process in which the market returns cause the fund flows at the same time that the flows cause the returns.

For our analysis, it is important to distinguish among various notions of correlations between flows and returns. For instance, Warther (1995) has documented strong correlations between monthly market returns and monthly aggregate mutual fund flows. The question then arises, Do such monthly correlations reflect causation between returns and flows? If they do, could they lead to astrong positive-feedback process?

Note that the correlations that Kaufman (1994) and Hale (1994) have in mind may be quite different. Kaufman, for example, emphasizes that the average investor in mutual funds has never experienced a prolonged bear market. In such a market, investors may suddenly react by redeeming their shares heavily. The correlation would therefore be between returns over an unspecified period and flows over a somewhat shorter period. Our analysis examines only monthly flow-return correlations from 1986 to 1996, a period for which there may not have been a bear market of long enough duration to test Kaufman’s hypothesis.

MEASURING MUTUAL FUND FLOWS

To measure mutual fund flows, we use monthly ICI data on cash flows into and out of mutual funds from July 1986 to April 1996.5 In the ICI data, cash flows are computed for each of the twenty-one groupings of funds by investment objective.

Within each group, cash flows are further broken down into total sales, redemptions, exchange sales, and exchange redemptions. Total sales and redemptions represent outside flows, while exchange sales and exchange redemptions represent flows between funds within a fund family. We compute net flows as total sales minus redemptions, plus exchange sales minus exchange redemptions.

We make several adjustments to the mutual fund categories by either aggregating categories or excluding some from our study. We exclude money market mutual funds and precious metal funds because they do not seem to be subject to the same risks as stock and bond funds. We also exclude various hybrid funds (flexible portfolio, income mixed, balanced, and income bond) because of the lack of an appropriate market price index.

We combine aggressive growth and growth stock funds, income and growth-and-income stock funds, and global and international stock funds. Hence, we collapse six equity categories into three: growth, income, and global stock funds. We also combine long-term municipal bond and state municipal bond funds into a single cate-gory of municipal bond funds. We retain four other bond fund categories: government bond, corporate bond, Government National Mortgage Association (GNMA) bond, and high yield bond.

We use growth stock funds as the benchmark stock fund and govern-ment bond funds as the benchmark bond fund. To control for the flows’ strong rising trend during the period, we normalize the flows by dividing them by the funds’ net asset value in the previous month. Flows are thus stated as a percentage of a fund category’s net assets.

Over the period, global stock funds and corporate bond funds received the largest net flows relative to net assets, while government bond funds received the smallest. Global stock funds and GNMA bond funds had the most volatile net flows, while income stock funds had the most stable flows. All the flows exhibit high autocorrelations, with government bond funds and GNMA bond funds showing the most persistent flows. These autocorrelations imply that large components of the flows are predictable on the basis of past flows.

To divide the flows into expected and unexpected components, we regress flows on three months of lags and on a time trend. The predicted values from the regressions then serve as our expected flows and the residuals as our unexpected flows. The expected flows for growth stock funds and government bond funds reflect a relatively smooth and slow process, while the unexpected flows show a great deal more short-run volatility.

MEASURING MARKET RETURNS

To measure market returns, we select market price indexes to gauge the performance of the markets in which the funds in each group invest. Within each group, some funds will do better than others, and flows may shift to the best performers. However, we are more interested in the aggregate flows, which depend not on the performance of specific portfolios but on that of whole market sectors.

In choosing among the various market indexes, it is not critical that we select precisely the right index because the various stock market indexes tend to be highly correlated, as do the bond market indexes.

We compute returns as the changes in the arithms of the end-of-month market indexes and alize them by multiplying by twelve. As a result, the annualized return for market i for month t would be given by R it = 12 (log P it - log P i,t-1 ), where P it represents that market’s index at the end of month t. We then compute log-excess returns as the difference between this market return annu-and the yield on prime thirty-day commercial paper (CP) in the previous month. The CP rate tracks returns on money market mutual funds, which are the natural alternative for an investor not wishing to invest in stock or bond funds.

CORRELATIONS BETWEEN RETURNS AND FLOWS

In general, net flows into the various mutual fund groups are highly correlated with market performance. The correlations between net flows and market returns range from 12 percent for government bond funds to 72 percent for high yield bond funds. In most cases, these correlations can be attributed almost entirely to the unex-pected component of net flows. The correlations between returns and the unexpected components range from 31 per-0 cent for GNMA bond funds to 71 percent for growth stock funds. We plot these correlations for government bond funds and growth stock funds, which serve as our benchmark bond and stock funds. In contrast, the correlations between returns and the expected components of net flows are by and large not statistically different from zero.

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