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Working Papers
* Presentations: 16th Annual Hedge Fund Conference (2025, Dauphine), 2025 Midwest Finance Association, 2025 FSU Truist Beach Conference, Catholic University of Portugal, NOVA University, 2024 Annual Valuation Workshop (Wharton), 2024 Wabash River Conference (Purdue)
Abstract:
We study the role of institutional investors’ subjective risk premia in explaining variation in their subjective expected returns (both over time and across investors). Our analysis uses long-term Capital Market Assumptions from asset managers and investment consultants from 1987 to 2022. Perceived market risk premia account for most of the countercyclicality and overall time variation in subjective expected returns, with the remainder driven by alphas (perceived mispricing). The risk premia effect stems almost entirely from time variation in perceived risk quantities rather than risk price (risk aversion). Additionally, market risk premia explain most of the expected return disagreement, but here alphas play a significant role, and risk price and risk quantities contribute roughly equally to the risk premia effect. These results provide benchmark moments that asset pricing models should match to be consistent with institutional investors’ beliefs.
Journal of Finance, Revise & Resubmit
* Media Coverage: AQR Research, Antti Ilmanen (April 2025); Invesco Risk & Review (June 2024)
* Presentations: 2024 Finance Conference at WashU, 2024 Northern Finance Association, 2024 European Finance Association Annual Meeting, 2024 Alpine Finance Summit, 2024 University of Washington Summer Finance Conference, 2024 Helsinki Finance Summit, 2024 Northern Finance Association, 2024 Financial Intermediation Research Society (FIRS), Adam Smith Workshop 2024 (LSE), 2024 AFA Annual Conference, 2023 Tel Aviv University Finance Conference (canceled), 2023 EUROFIDAI – ESSEC Paris December Finance Meeting, 2023 INSEAD Finance Symposium, 2023 USC Finance Workshop on Valuations, Arizona State University, Norwegian School of Economics, Penn State University, Purdue University, Rutgers University, The Ohio State University, University of Southern California, University of Notre Dave, Vienna Graduate School of Finance.
Abstract:
We use the long-term Capital Market Assumptions of major asset managers and institutional investor consultants from 1987 to 2022 to provide three stylized facts about their subjective risk and return expectations on 19 asset classes. First, there is a strong and positive subjective risk-return tradeoff, with most of the variability in subjective expected returns due to variability in subjective risk premia (compensation for market beta) as opposed to subjective alphas. Second, belief variation and the positive risk-return tradeoff are both stronger across asset classes than across institutions. And third, the subjective expected returns of these institutions predict subsequent realized returns across asset classes and over time. Taken together, our findings imply that models with subjective beliefs should reflect a risk-return tradeoff. Additionally, accounting for this subjective risk-return tradeoff when modeling multiple asset classes is even more important than incorporating average belief distortions or belief heterogeneity in
our setting.
* Presentations: 2024 Ohio State Real Estate Research Symposium, 2024 AREUEA-ASSSA (San Antonio), 2023 IPC Spring Research Symposium (University of North Carolina, Chapel Hill); 2023 FSU-UF Critical Issues in Real Estate Symposium (Florida State University)
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Abstract:
Illiquid assets have stale prices and spurious return autocorrelation. It is important to understand what drives this autocorrelation. I provide evidence that the fundamental driver of this phenomenon is the difficulty in valuing illiquid assets and not managerial manipulation. Specifically, I find that autocorrelations, risk factor loadings, (β’s) and risk-adjusted returns (α’s), are all statistically and economically equivalent, regardless of whether valuations are completed internally or externally. I do find, though, that internal valuations incorporate market pricing information at a slower rate than external valuations. This is because internal valuations have a larger percentage of lame valuations. However, contrary to the general consensus, this actually decreases the smoothing effect because the percentage of lame valuations is time-varying making returns lumpier than they would be otherwise. Similarly, I find that external valuations have larger loadings on lagged factors as well as larger valuation updates. However, after controlling for lame valuations, I find there is no material difference between internal and external valuations for either of these metrics. Lastly, I find that managers and third-party appraisers both put forth the greatest valuation effort when market returns are the most extreme.
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