JOIM: 2026
Volume 24, No. 1, First Quarter 2026
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Practitioner's Digest
Practitioner’s Digest • Vol. 24, No. 1
The “Practitioner’s Digest” emphasizes the practical significance of manuscripts featured in the “Insights” and “Articles” sections of the journal. Readers who are interested in extracting the practical value of an article, or who are simply looking for a summary, may look to this section.
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Article
Do Bubbles Exist? Positive Digital Asset Market Prices are the Definitive Proof
Many economists believe that asset price bubbles don’t exist or that, due to a joint hypothesis, they are difficult if not impossible to empirically validate. This paper dispels this belief by providing definitive proof that bubbles exist for a set of digital assets that have no cash flows and a zero liquidation value, but trade with positive market prices.
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Article
Target Date Funds: An Analysis of Strategies and Performance
Target date funds (TDFs), which seek to provide a broad demographic of individuals with a long-term retirement investment solution, play a major role in defined contribution (DC) retirement plans, and have also attracted substantial assets from investors in other types of accounts. Further, most DC plan investment menus designate TDFs as the default investment. This paper provides an overview of the strategies and structures of TDFs, as well as current trends among major TDF providers. We also document substantial heterogeneity across TDFs, and provide guidance on how to evaluate the quality of TDFs in light of this heterogeneity.
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Article
Deleveraging CAPM: Asset Betas vs. Equity Betas
The classic estimates of CAPM equity betas are notoriously unstable. We assume that this is mainly due to changes in firms’ leverage over time. In order to take leverage into account, we propose a new approach where asset correlations among firms are pairwise constant, while equity correlations change over time as a function of the stochastic evolution of firms’ asset values. The paper closes with a simulation that helps to show the model’s features
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Article
Universe-Gaming and Recommendation-Herding in Aggregate Bonds
In a sample of 154 Aggregate Bond portfolios, fifteen percent have greater Single B credits and outperform. Another third has a greater chance of being recommended to the investor. The former involves gaming, the latter, herding. An investment intermediary penalizes ‘universe-gaming’ but that leads to congregated recommendation for underperforming managers. This asymmetry in utility stresses performance when credit spreads narrow and recommendation when they widen. Larger fund size investors benefit in marginal utility. In down markets investors may select to hold on to ‘out-recommended’ underperformers and sell outperformers, worsening return instability.
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Book Review
The Behavioral Economics and Politics of Global Warming
Book Review, Mark Kritzman
Volume 24, No. 2, Second Quarter 2026
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Article
Adapting to AI: Rethinking Labor Income and Retirement Design in a Changing Economy
In this paper, we discuss how artificial intelligence (AI) could impact lifetime income through the channel of occupational tasks and wages. We first derive a life-cycle model of consumption, then incorporate AI as a shock to income and longevity. We find that AI-derived impacts on labor income and longevity can influence wealth accumulation and consumption over an individual’s lifetime. We test a key input to this model in which occupations that experienced a net drop in tasks demanded of workers suffer declines in total wages. We then use a large language model (LLM) to estimate how susceptible occupations can be to task reduction from automation. Our results suggest that most occupations will be affected by AI-driven automation but with a wide dispersion across jobs and industries. We conclude with a discussion on why AI-driven changes in the labor market should prompt new approaches to retirement and explore how financial planning can help workers adjust to an AI-enhanced economy.
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Article
A Tail of Five Skews
We show that a highly statistically significant total skewness risk premium is embedded in the cross-section of returns within a large universe of multi-asset futures and forwards, within a broad set of 215 long/short style factors formed on that universe, and within the cross-sectional equity factor zoo. The skewness risk premium is most robust when it is measured in a relatively new, intuitive way that minimizes the impact of outliers while still capturing information in the tails, which we demonstrate by evaluating five candidate methods across a battery of empirical tests. We show there is compensation for bearing skewness risk in both the long run and ex ante on a point-in-time basis available to investors.
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Survey & Crossover
Option Return Anomalies
This paper surveys empirical option return anomalies in both unhedged and delta-hedged strategies. We document persistent deviations from classical models, including the sharply negative returns on out-of-the-money puts, the negative performance of zero-beta straddles, and the large losses of delta-hedged portfolios documented in many studies. These patterns remain difficult to reconcile because most option-pricing models provide valuation formulas but not the formulas for finite-horizon expected returns or higher-order return moments. Equivalent Expectation Measures (EEMs) and Multiverse EEMs (MEEMs) supply closed-form expressions of these moments, enabling cleaner comparisons between model-implied and realized returns. We outline how these tools can be used to address longstanding anomalies and highlight future research opportunities for explaining cross-sectional predictability, volatility risk premia, and finite-horizon option returns.