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Working Papers

* Presentations: 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 Notre Dave, Vienna Graduate School of Finance.

Figure9_riskPremiaVsBeta_CAPM_scatter.png
Figure15_dataVsBeliefs_Er_scatter.png

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.

Revise & Resubmit

* Presentations: Midwest Finance Association, FSU-UF-UCF Critical Issues in Real Estate Research Symposium, FMA Annual Meeting, Conference, Pitt/OSU/Penn State/CMU Finance Conference (Carnegie Mellon), 10th Annual Hedge Fund and Private Equity Conference (Dauphine), University of Cincinnati, Cornell University, the University of Melbourne, the University of Notre Dame, The Ohio State University, Santa Clara University, the Office of Financial Research, the University of Southern California, the University of Virginia.

Figure 4aaa - Q-adjusted Return Quintile
Figure 3 - Queue Quintiles.png

Abstract:
Open-end funds provide a liquidity transformation service by issuing and redeeming shares that are more liquid than their assets. However, because these assets are illiquid, managers need time to transfer capital to the underlying market. Liquidity buffers and liquidity restrictions enable this. Additionally, because of this illiquidity, their returns are predictable and susceptible to NAV-timing strategies which transfer wealth. I show NAV-timing strategies appear profitable on paper and investors appear to follow these strategies. I also show liquidity restrictions protect against these NAV-timing risks while liquidity buffers do not. In fact, liquidity buffers amplify them when added to liquidity restrictions.

* 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)

Figure 1 - External vs. Internal Indexes (A).png
Figure 1 - External vs. Internal Indexes (B).png

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.

* Presentations: 2024 AREUEA National Conference (Washington DC), 2024 IPA Research Conference

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Abstract:
Private Commercial Real Estate (CRE) funds provide institutional investors an opportunity to access the CRE market, but most of them are inaccessible to typical individual (retail) investors. In this paper, we study the early performance (2016 to 2023) of a special and emerging class of non-listed CRE funds that are accessible to individual investors. These funds, referred to as Net Asset Value (NAV) Real Estate Investment Trusts (REITs), have grown in importance over the last decade. They now represent a major alternative to publicly traded REITs in providing individual investors a way to access CRE investments without direct ownership. We find that the observed returns from these NAV REITs suffer from smoothness due to lagged pricing updates, and thus unsmoothing returns is important for studying their risk-adjusted performance. We then show that NAV REITs have delivered large alphas relative to public indices over our sample period. Finally, we highlight that traditional alpha analysis may not be adequate for a short sample like ours and provide an alternative alpha analysis that indicates the alphas of NAV REITs over our sample period were economically meaningful, albeit substantially lower than traditional alpha analysis suggests.

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