Optimal portfolio and spending rules for endowment funds

Muhammad Kashif (), Francesco Menoncin () and Iqbal Owadally ()
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Muhammad Kashif: University of Brescia
Francesco Menoncin: University of Brescia
Iqbal Owadally: Cass Business School, City, University of London

Review of Quantitative Finance and Accounting, 2020, vol. 55, issue 2, No 9, 693 pages

Abstract: Abstract We investigate the role of different spending rules in a dynamic asset allocation model for university endowment funds. In particular, we consider the fixed consumption-wealth ratio (CW) rule and the hybrid rule which smoothes spending over time. We derive the optimal portfolios under these two strategies and compare them with a theoretically optimal (Merton) strategy. We show that the optimal portfolio with habit is less risky compared to the optimal portfolio without habit. A calibrated numerical analysis on U.S. data shows, similarly, that the optimal portfolio under the hybrid strategy is less risky than the optimal portfolios under both the CW and the classical Merton strategies, in typical market conditions. Our numerical analysis also shows that spending under the hybrid strategy is less volatile than the other strategies. Thus, endowments following the hybrid spending rule use asset allocation to protect spending. However, in terms of the endowment’s wealth, the hybrid strategy comparatively outperforms the conventional Merton and CW strategies when the market is highly volatile but under-performs them when there is strong stock market growth and low volatility. Overall, the hybrid strategy is effective in terms of stability of spending and intergenerational equity because, even if it allows short-term fluctuation in spending, it ensures greater stability in the long run.

Keywords: Spending rules; Endowments; Bellman’s equation; Asset allocation (search for similar items in EconPapers)
JEL-codes: C61 G11 G23 (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (1)

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DOI: 10.1007/s11156-019-00856-x

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