CFA Institute

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The latest Middle East flare-up has once again put theoretical asset pricing at odds with how markets actually clear: prices can move violently even when long-run fundamentals have not obviously changed. In calm regimes, the textbook framework, risk premia as compensation for bearing systematic risk, does a respectable job of organizing returns. But in stress, a different mechanism often dominates. Prices clear less as a referendum on fair value and more as a function of constraints: leverage, margining, liquidity, mandates, and who is forced to transact first. In those moments, equilibrium is less about consensus and more about balance-sheet capacity. For institutional investors and the investment professionals serving them, the implication is practical. A mispricing is only an opportunity if it can be held until it closes. The relevant horizon is not valuation, but funding and governance. In practice, this shows up in a few consistent shifts: You stop treating volatility as a sufficient measure of risk. Variance is a statistic. Investor pain is often driven by fragility — the interaction of leverage, liquidity, path dependency, and funding terms. In the gilt episode, the defining risk was not that yields moved, but that the move triggered collateral calls and forced sales in an illiquid market. You stop treating “cheap” as inherently actionable. A mispricing is only an opportunity if you can survive the path to convergence. The relevant horizon is not valuation, but funding and governance. Capacity is not a “risk overlay”; it is part of the edge. You reinterpret cash and patience as optionality. In a consensus-clearing world, holding cash can feel like an admission of analytical defeat. In a balance-sheet-clearing world, cash is an intentionally held option, it allows you to provide liquidity when others are forced to sell. The right question is not “why aren’t we fully invested?” but “are we paid for the fragility we are underwriting, and can we hold it when it bites?” You treat governance as a market variable. Many institutions treat liquidity as an attribute of the asset. In practice, liquidity depends on who needs to trade at the same time and whether your decision-making can respond at the speed the regime demands. Governance latency is not a cultural issue; it is a risk parameter. source

In this conversation with Frank Fabozzi, CFA, Tasitsiomi explains that sophisticated models add value only when paired with well-defined problems and high-quality data. Echoing Einstein, she argues that models should be made as simple as possible, but not simpler. She also shares when advanced machine learning techniques are most effective, particularly for capturing nonlinear relationships, working with unstructured data, or enabling unsupervised discovery. Key Discussion Points Principle of parsimony: When the simplest model preserves essential insights and helps avoid unnecessary complexity, cost, and risk. Poke the model: Why probing model behavior, especially outside normal conditions, helps investment teams understand potential risks and failure modes. Understand the tools: Why sound judgment about data, assumptions, and model limitations matters more than coding skills, especially for younger analysts building credibility on AI-enabled investment teams. Speak the language: Why successful AI adoption requires both technical rigor and clear communication across investment teams. See  all episodes  source

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Is this the end of deep, liquid markets? Not quite—but the model has changed. Liquidity is no longer an abstract concept; it is being tested in real time. Private markets are illiquid; this is well understood. The issue is that liquidity is increasingly engineered at the product level, often creating expectations that may not hold under stress. This is a subtle but important shift—from an asset characteristic to what a product promises. Practitioners used to ask: How liquid is this asset? Now they should ask: How is this product making it seem liquid—and when does that break? We see it in redemption pressure across private credit. The broader ecosystem is showing signs of strain: business development companies (BDCs) are trading at persistent discounts to net asset value (NAV), withdrawals are being gated, capped, or delayed, secondary markets are clearing at discounts, and fundraising has slowed alongside weaker distributed to paid-in capital (DPI). These are not isolated dislocations; they reflect a change in how liquidity is being designed and delivered. What once felt like a stable feature of markets is now proving to be conditional, and increasingly fragile under stress. source

GenAI is transforming investment workflows, raising critical questions about human judgment, task design, and the future of the profession. This blog by Rhodri Preece, CFA, was published on the heels of AI in Asset Management: Tools, Applications, and Frontiers. The AI in Asset Management book was a joint initiative between the CFA Institute Research Foundation and Research and Policy Center that includes contributions from experts around the globe. Each chapter is supported by a Practitioner Brief delivering role-specific insights in a digestible format.  Read the blog. source

Retail access to private credit and private equity strategies is expanding globally. These assets may offer diversification and return potential, but they introduce risks that differ fundamentally from public markets. The most underappreciated is valuation lag. Unlike publicly traded assets that are continuously marked to market, private assets are typically marked to a model and updated periodically. During periods of volatility, reported net asset values may lag materially behind economic reality. This creates two concerns. First, reported performance may appear smoother than underlying risk warrants. Second, stale pricing can create arbitrage opportunities: informed investors may redeem at outdated valuations, transferring losses to those who remain once adjustments occur. Recent market episodes suggest that retail investors are often less prepared for the illiquidity, gating mechanisms, and valuation discretion embedded in private strategies. Strong valuation governance is therefore essential. Independent oversight, periodic external reviews, and transparent disclosure of methodologies are not procedural formalities. They are safeguards against unfair outcomes and erosion of investor confidence. source

Christos Antoniadis and Spyros Skouras Daily hedge fund return data uncovers more factors, lower alpha, and greater time-varying exposures than monthly data suggests — revealing that investors gain far better insights and improved portfolio decisions with higher-frequency information. source