Key themes in the most-read blogs published on Enterprising Investor between July 1 and September 30 include warnings signs in private markets, positioning for Fed pivots, testing new AI tools in research and portfolio construction, and reinforcing governance and philosophy to stay resilient through uncertainty.
Resilience Over Prediction: Whether in response to Fed timing, inflation expectations, or market cycles, this quarter’s most popular blogs emphasize portfolio durability, diversification, and structural strength amid uncertainty.
A Smarter Use of Metrics and Tools: From capital deployment factors in private equity to ML-driven portfolio construction and private GPTs for research, investors are rethinking how they measure, analyze, and act on information.
Integrating Macro, Technology, and Governance: Today’s investment edge comes from connecting macro context, technological innovation, disciplined governance, and coherent philosophy to achieve consistent long-term results.
The warning signs are piling up. From valuation inflation to fee extraction on unrealized gains, today’s market bears striking resemblance to the late stages of past financial manias, writes Mark J. Higgins, CFA, CFP. This post draws on financial history to show how those patterns are resurfacing in private markets.
Bill Pauley, CFA, Kevin Bales, CFA, Adam Schreiber, CFA, CAIA, and Ty Painter review Fed hiking and easing cycles since 1965 to show why policy pivots don’t provide a simple playbook. Out of 12 hiking cycles, 10 saw yield-curve inversions and eight ended in recessions. Even preemptive rate cuts do not always avoid a recession.
Cash, bonds, and gold have their perks, but the downside can be severe, writes Pim van Vliet, PhD. Shares of low-volatility companies with earnings that can grow with inflation may lag in bull markets but historically cushion drawdowns and may deliver long-term returns. When blended well into a portfolio, they can improve downside risks without relying solely on bonds.
Baridhi Malakar, PhD, outlines how to set up a practical, privacy-preserving AI research assistant in an open-source environment. The benefit is a secure, cost-effective, and fast way to parse thousands of pages in seconds as part of the research process while maintaining governance and IP protection.
Xavier Pintado, PhD, and Jérôme Spichiger, CIIA, argue that private equity firms’ performance metrics do not include idle capital, which can be substantial. More precise metrics are the capital deployment factor (CDF), and the Orbital Assets Method (OAM), which treats the investor capital holistically with outcomes comparable to public markets.
Forecasts and surveys show that both professionals and consumers get it wrong when predicting inflation, write David Blanchett, PhD, CFA, CFP, and Jeremy Stempien. Real assets (commodities, listed infrastructure, REITs) may look inefficient when inflation is low, but their portfolio value appears when inflation surprises to the upside.
Riding out volatility is often critical to achieving long-term success in the markets and history provides a lesson to that end, write Bill Pauley, CFA, Kevin Bales, CFA, Adam Schreiber, CFA, CAIA, and Ty Painter. After evaluating 15 bear markets using the S&P 500 since 1950, they conclude that low volatility and dividend investment styles endure irrespective of recessionary conditions.
Winston Ma, CFA, Esq, explores how the emergence of a US sovereign wealth fund could upend markets, unearthing both risks and opportunities, particularly as it reshapes strategic sectors like semiconductors, artificial intelligence, and rare earths.
Mark Armbruster, CFA, examines the reasons for underperformance among nonprofit and endowment portfolios. Among them: costly alternatives and governance issues. His suggested remedies include adopting a deliberate, long-term investment philosophy and setting limits on certain asset classes.
Investment management firms who adopt and train machine learning (ML) tools will maintain a competitive edge over their peers in portfolio construction and performance, argues Michael Schopf, CFA. ML methods better capture non-linear risks and can more quickly assess a group of stocks under various market conditions and improve diversification.
Looking Ahead
Together, these Q3 blogs show how investors are adapting to a fast-changing environment, learning from past rate cycles, experimenting with AI and machine learning in research and portfolio design, and reinforcing the value of resilient, well-governed investment approaches. In world shaped by policy shifts and technological disruption, adaptability grounded in sound philosophy remains investors’ best advantage.
