Minimization of funding volatility in the endowment funds of charitable organizations should be considered from a total wealth perspective. Generally, only investable financial assets are considered, whereas other important assets, such as owned real estate, donation revenue, and program service fees, are ignored. The author focuses on the volatility associated with donation revenue.
The author argues that a total wealth perspective should be considered when determining the optimal endowment portfolio for charitable organizations. He focuses on the risks associated with different types of charitable donations to construct the optimal portfolio to minimize a charity’s funding volatility.
He demonstrates that donation risk has statistically significant relationships with market factors (i.e., there is a likelihood of a change in donor behavior given a change in market conditions). Thus, the optimal allocation for an endowment depends on the different types of donation risk, the proportion of revenue streams of the charity funded by the endowment, and the organization’s level of risk aversion.
How Is This Research Useful to Practitioners?
This research pertains to investment practitioners who are involved in the management of endowment funds, even if only in an advisory capacity. The significance of the research arises from the fact that funding volatility may ultimately lead to a charitable organization’s failure to fund its mission. But if the organization’s assets (particularly donations) are unaccounted for, it could lead to underutilization of the assets, and the organization would thus operate at suboptimal levels, which is also undesirable. All significant financial and nonfinancial assets should be considered when constructing a charitable organization’s portfolio.
How Did the Author Conduct This Research?
Historical data are obtained for 40 years (from 1973 to 2012) on 11 types of charitable donations from the Giving USA 2013 Annual Report on Philanthropy. The data are analyzed based on sources of donation (four in total) and recipient of donation (six are identified). Furthermore, 14 asset classes are identified based on those commonly used by the investment community for building portfolios for their clients.
The author uses a seven-factor model based on the Fama–French five-factor model, which explains 54% of the variation in donation risk. The seven factors include the market factor, which is the difference in returns on the stock market and the risk-free rate; the size factor, which is the difference between the returns on small- and large-cap stocks; and the value factor, which is the difference between returns on value and growth stocks. Past data for these three factors are obtained from Kenneth French’s data library. The bond duration factor is calculated as the difference in returns on the Ibbotson Long-Term Government Bond Index and the Ibbotson 30-Day US Treasury Bill Index. The bond default factor is the difference between the returns on the Ibbotson Long-Term Corporate Bond Index and the Ibbotson Long-Term Government Bond Index. Data for the momentum factor are obtained from Kenneth French’s data library and data for the liquidity factor are obtained from Lubos Pastor’s website.
After conducting the seven-factor analysis, the author runs portfolio optimization routines to determine asset class weights that minimize donation risk. Optimal weights are shown to vary by as much as 25% compared with analysis that does not consider donation risk.
The ability of an endowment to attract donations cannot be ignored as an asset of the endowment when constructing an optimal portfolio. Therefore, the associated risk also needs to be accounted for to arrive at an optimized portfolio.