Measuring the Ivy 2017: Dartmouth vs. Harvard, Similar Exposures Yield Significantly Different Results
The returns of endowments can be attributed to two fundamental components: asset allocation and security selection. Asset allocation is what a factor model is generally able to explain, shown in terms of factor exposures.
With the first two Ivy League endowments turning in their fiscal year 2017 returns, we’re providing a snapshot to compare how Harvard and Dartmouth did relative to each other using our patented Dynamic Style Analysis (DSA) model. DSA is an enhanced (returns-based) quantitative analysis model that provides a more transparent view of opaque or complex investment strategies, funds and products.1
This article is a preliminary post to the forthcoming MPI Ivy League endowment performance comparison report for fiscal year 2017. That report will publish in the fourth quarter, once the endowment reporting period is complete. In the meantime, you can find out how the Ivy League endowments did in previous years by reading MPI reports for fiscal year 2015 and 2016.
Measuring Endowment Returns
The returns of endowments can be attributed to two fundamental components: asset allocation and security selection. Asset allocation is what a factor model is generally able to explain, shown in terms of factor exposures. Security selection is determined by the performance of securities selected by the managers that the endowments invest in. One thing to note: since the endowment fund returns we use in our analysis are net of fees, negative selection can arise due to fees that the endowments pay to their managers.
With that in mind, the most interesting observation in comparing Harvard―which returned 8.1 percent for the 2017 fiscal year―to Dartmouth―which returned 14.6 percent―is that, absent the impact of selection return (represented by the blue bars in the below chart), their performance should have been on par with each other, indicating that neither endowment owned a clear asset exposure advantage.
In fact, the contribution of each asset class to the overall performance was similar across both funds, with the exception of natural resources (in green below). It is the selection return that is responsible for the majority of their performance difference. Harvard displayed a selection return of -5.4 percent during fiscal year 2017, while Dartmouth displayed a selection return of 1.05 percent during the same period.
In his 2017 fiscal year letter, Narv Narvekar, CEO of Harvard Management Company, pointed to a number of internal changes enacted during the year, which included markdowns of natural resources; unloading private equity, venture capital and real estate funds in the secondary market; and increased allocations to external managers.
The recent changes at Harvard seem to be the driving force behind what the data show, since Harvard and Dartmouth have historically tracked very closely against their respective factor mimicking portfolios (see below chart). Given this, one could view Harvard’s 2017 performance as an anomaly that should go away once changes under the leadership of Mr. Narvekar are fully implemented.
Footnotes
- 1 DISCLAIMER: MPI conducts performance-based analyses and, beyond any public information, does not claim to know or insinuate what the actual strategy, positions or holdings of the funds or companies discussed are, nor are we commenting on the quality or merits of the strategies. This analysis is purely returns-based and does not reflect actual holdings. Deviations between our analysis and the actual holdings and/or management decisions made by funds are expected and inherent in any quantitative analysis. MPI makes no warranties or guarantees as to the accuracy of this statistical analysis, nor does it take any responsibility for investment decisions made by any parties based on this analysis.
My goodness, those were expensive internal changes at Harvard! Hard to imagine they were necessary to implement in such draconian fashion.
That may be true, Charles. That can be a downside to investing in illiquid assets, trying to sell off a large amount of them in a short time frame can have a significant impact on asset values.