The Journal of Investment Management • [email protected](925) 299-78003658 Mt. Diablo Blvd., Suite 200, Lafayette, CA 94549 • Bridging the theory & practice of investment management

Bridging the theory & practice of investment management

JOIM: 2026

Volume 24, No. 1, First Quarter 2026

  • 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.

  • 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.

  • 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.

  • 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

  • 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.

  • Book Review

    The Behavioral Economics and Politics of Global Warming

    Book Review, Mark Kritzman

Volume 24, No. 2, Second Quarter 2026

  • Practitioner's Digest

    Practitioner’s Digest • Vol. 24, No. 2

    The “Practitioners 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.

  • 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.

  • 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.

  • 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.

  • Survey & Crossover

    Fall 2025 JOIM Conference Summaries — McCombs School of Business, University of Texas at Austin

    We showcased members of the McCombs School of Business faculty alongside outstanding presenters and discussants from other finance institutions, focusing on selected topics of timely interest. This provided a platform highlighting several areas of cutting-edge research. Our emphasis was on topics of strong practical significance addressed by leading researchers in finance.

  • Case Study

    Holistic Sustainability: Identifying “Clean” Investments in a Fragmented Disclosure Framework

    "Case Studies” presents a case pertinent to contemporary issues and events in investment management. Insightful and provocative questions are posed at the end of each case to challenge the reader. Each case is an invitation to the critical thinking and pragmatic problem solving that are so fundamental to the practice of investment management.

  • Book Review

    Skill Versus Luck: Taking the Guessing Out of Equity Fund Selection

    “Book Reviews” identifies important, and often popular, new books from a wide range of investment topics. Beyond providing a summary and review of the content and style of the books, “Book Reviews” seeks to contribute to a conscious, critical, and informed approach to investment literature.

Volume 24, No. 3, Third Quarter 2026

  • Article

    Advances in Corporate Credit Modeling: From Valuation to Portfolio Theory

    Corporate bond markets have grown into a core component of global financial systems and institutional portfolios, yet the academic literature has progressed unevenly across pricing, empirical return behavior, and portfolio construction. This paper provides a comprehensive survey of corporate bond research, spanning structural, reduced-form, and hybrid pricing models; empirical evidence on default, recovery, liquidity, and return predictability; and portfolio-oriented approaches used in both academic and practitioner settings. We identify a central gap in the literature: while pricing theory operates largely under the risk-neutral measure and empirical studies document return behavior under the physical measure, these strands have not been fully integrated into a unified portfolio framework. In the final part of the paper, we show how the Equivalent Expectation Measures and multiverse EEMs provide analytical tools for deriving finite-horizon expected returns and variance–covariance matrices of corporate bond returns under the physical measure, enabling direct application of classical mean–variance analysis to construct efficient frontiers and ex-ante Sharpe-ratio-maximizing portfolios for risky corporate bonds.

  • Article

    Estimating Industry Betas via Machine Learning: Promises and Pitfalls of Multi-Output Predictions

    This study examines the predictive performance of multi-output machine learning models in estimating industry betas. Multi-output predictions improve forecast accuracy by identifying cross- sectional interdependencies between industries that single-output approaches systematically overlook. Two portfolio applications demonstrate the economic value of these improvements: constructing market-neutral anomaly strategies and optimizing minimum variance portfolios. Our results demonstrate that multi-output estimates facilitate a more detailed modelling of systematic risk. This has a meaningful impact on investment decisions, leading to more effective hedging strategies, improved risk management, and greater alignment with investor preferences.

  • Survey & Crossover

    Biblically Responsible Investing: Methodology and Evidence

    Does Biblically Responsible Investing (BRI) impose a financial penalty? Analyzing BRI exchange-traded funds (ETF) against conventional benchmarks using academic literature and market data from 2014–2025, we find no systematic underperformance. Performance varies across funds: the Inspire Small/Mid Cap ETF (ISMD) demonstrates superior risk-adjusted metrics (Sharpe 0.65, alpha 2.19), while others lag. However, fees warrant scrutiny—BIBL (0.39%) and ISMD (0.57%) exceed index fund costs, though strong performance has largely justified them. RISN’s 0.79% fee, given only modest returns, raises concerns. With 92% of over 30,000 global companies passing biblical screens, diversification concerns are unfounded. BRI enables faith alignment without systematically sacrificing returns.