CFA Institute

A few years ago, I transferred-in an account for a client. As I looked through the positions to prepare recommendations about which positions to sell and which to keep, I noticed a handful of penny stocks. Actually, to call them penny stocks would be an exaggeration. They were each worth fractions of a penny and, of course, only traded over-the-counter. I assumed that these were positions-gone-bad—stocks that had fallen far from grace, trophies to amateur overconfidence. I called my client to discuss removing them. “…Oh, and one more thing. I’ll send you a form to remove these stocks from your account since they don’t trade and aren’t worth anything.” “What?! No, don’t do that!” was his urgent reply. “Those are my lottery tickets! I put about a hundred bucks into each of them and I want to see if they pay off!” I chuckled. “Alright, no problem, we’ll leave them, but I’m not going to follow them, okay? Just let me know if you change your mind.” I didn’t know it then, but I gave him terrible advice that day. In fact, I should have been the one to tell him to put some money in those micro-penny stocks. * * * Before you excommunicate me as a heathen, at least hear me out. Let’s take a step back and remember where the advice “never gamble” comes from. A standard utility function taught in the CFA Program curriculum (sometimes called quadratic utility) determines an investor’s happiness from her portfolio’s expected return, minus the variance (volatility) of those returns, times her risk aversion parameter. The more averse to risk, the more unhappy she is with variance (volatility). In this model, all else equal, higher volatility is always bad. In this model we would never expect an investor to choose a high volatility, low-return portfolio (i.e., a gambling portfolio) when low-volatility, high-return portfolios are on offer. We have this expectation because this model assumes that the thing our investor wants to avoid is volatility. By contrast, goals-based theories of choice take a different approach. Rather than define risk as volatility, goals-based utility defines risk as “not having the money you need when you need it,” to quote my friend Martin Tarlie. Risk, in goals-based investing, is not volatility, but the probability that you fail to achieve your goal.  Running with this more intuitive definition yields some surprising results because it changes the math of the portfolio choice problem. We move from an equation in which return and volatility are the only two variables, to a probability equation of which return and volatility are inputs, but not the only inputs. All the variables which define our goal (minimum wealth level, time horizon, current wealth, etc), are also inputs in the probability equation. Lastly, when we remove the inexplicable academic assumption that investors can borrow and sell short without limit, then we find that the efficient frontier has an endpoint, the last efficient portfolio. Here’s the catch: sometimes, investors have return requirements that are greater than what the last efficient portfolio can offer. When that happens, her probability of achievement is maximized by increasing variance rather than decreasing it, even if returns are lower. And so we enter the world of rational gambles. Rational gambles are those portfolios to the right of and below the last efficient portfolio, but for which the probability of achievement continues to rise. Irrational gambles are those for which the probability of achievement begins to fall. The plot below illustrates the point. source

Futures offer significant advantages in execution speed. When regime shifts require exposure adjustment, physical holdings impose transaction costs, potential tax triggers, and multi-day settlement periods. Futures adjustment occurs in minutes at near-zero cost. A $300 million portfolio detecting rising volatility needs to reduce equity exposure from 70% to 55%, eliminating $45 million of exposure.Traditional rebalancing: sell $45 million in shares. Cost: 0.3% to 0.5% ($135,000 to $225,000). Time: two to three days. Via futures: eliminate $45 million of synthetic exposure. Cost: $1,000 to $2,000. Time: minutes. Adjusting exposure multiple times annually as regimes shift? The cumulative savings become substantial. More importantly, low adjustment costs remove hesitation. You can respond to changing conditions without worrying that reversal will be prohibitively expensive. This agility enables capturing opportunities in favorable regimes by increasing exposure when volatility is low and protecting capital in adverse regimes by reducing exposure when volatility spikes, exactly what’s needed to maintain long-term consistency. Implementation Risks The same principle applies beyond protection. Capital efficiency through derivatives isn’t without complications. Three risks require management: Margin Calls During Stress Futures require margin. When markets move sharply against positions, you need to add margin quickly, sometimes intraday. March 2020 taught this lesson clearly. Some institutional investors maintained minimal margin buffers. When requirements doubled or tripled overnight, liquidity squeezes forced liquidation at the worst possible moment. Mitigation: maintain 3x to 4x the margin requirement in liquid reserves. Use Treasuries as collateral; they’re accepted for margin and continue generating yield. Basis Risk Between Physical and Synthetic Futures don’t replicate indices perfectly, particularly during extreme volatility. S&P 500 futures tracking error ranges from 2 to 5 basis points in normal markets to 3 to 80 basis points during stress. For a $150 million position, that’s $45,000 to $120,000 in temporary divergence. Mitigation: limit synthetic exposure to 25% to 35% of equity allocation. Use only highly liquid futures on broad indices rather than sector-specific or small-cap contracts. Monitor basis daily and adjust if divergence becomes significant. Operational Requirements Adding a derivatives layer requires infrastructure: real-time exposure tracking, margin management processes, counterparty monitoring, regulatory reporting. This can seem daunting. But for insttutional investors already operating derivatives for hedging, adding an efficiency layer is incremental rather than transformational. The systems already exist. New to derivatives? Start with a single liquid instrument: S&P 500 futures representing 15-20% of equity allocation. Build comfort and establish processes over 6 to 12 months, then scale gradually.The complexity is real but proportionate.  Compared to 150 to 200 basis points in annual savings and materially improved risk-adjusted returns, the operational investment justifies itself, particularly when viewed as permanent infrastructure rather than temporary overlay. Decision Framework Three conditions indicate when this approach is most effective:Capital in Low-Return Positions. Maintaining 10% to 15% in defensive positions for operational or strategic reasons? Capital efficiency dramatically reduces opportunity cost. Already 100% invested comfortably? The savings are marginal. Rebalancing Frequency Volatility targeting, regime-based adjustments, tactical tilts — each imposes transaction costs. Physical rebalancing costs 20 to 50 basis points per adjustment. Derivatives cost 1 to 3 basis points. Quarterly rebalancing or less? Savings don’t justify added complexity. Monthly or more frequent adjustments? Annual savings reach 100 to 200 basis points. Operational Capacity Already using derivatives for hedging? Adding efficiency layers is natural. Without derivatives experience? Start small with gradual scaling to develop capability without excessive risk. source

Innovations are rarely just about superior performance. They are also about experimentation. And all new experiments breed their fair share of miscarriages. Given the extraordinary impact that financial leverage has on equity returns, PE fund managers have spent the past 40 years sharpening their use of debt funding. It is the area where the industry has witnessed the most innovation, because leverage is the principal means through which PE fund managers maximize returns3. Since the 2008 financial crisis, institutional lenders and PE firms have greatly benefited from increased regulation of the banking industry. In the past 15 years, they have grown their share of the corporate debt market. Large-cap PE firms are now among the largest corporate lenders: Apollo, Ares, Blackstone, Carlyle, and KKR all play on both sides of the capital structure4. That allows them to do two things. They can use their private debt divisions’ ability to underwrite loans as a bargaining tool when negotiating terms with third-party lenders, and they can acquire companies on the cheap by buying distressed debt at a discount, with the option of taking full control of the leveraged business if the latter defaults on its debt. Lender-led buyouts have become common. With so much spare capital in the financial system, borrowers are frequently granted exceedingly generous terms, including the ability to draw interest-only loans (meaning that the principal is only repayable upon the sale of the business or when the loans reach maturity) or without the need to meet strict financial ratios (debt covenants). Today, most buyouts with an enterprise value above $100 million are financed with covenant-lite bullet loans, meaning that the debt raised is not amortized but only repayable in full upon maturity or change of control, giving the borrower years to operate without constraint from its lenders. The golden rule is to keep debt as a proportion of total funding at a manageable level. Up to 60% seems to work for most sectors, unless they are subject to sudden regulatory changes, technological disruption, or fierce cyclical downturns, in which case leverage ratios should be set much lower5. The risk of default on debt obligations for many LBOs can be unusually high. Lengthy renegotiations with lenders, to amend covenants and extend maturities or, increasingly, via liability management exercises6, are just the start. Default can also lead to bankruptcy. That makes the adoption of best practice principles imperative. Since few deal targets ever meet all the criteria to qualify as perfect LBO candidates7, practitioners must embrace investment and management discipline that can weather the test of time. Parts of this post were adapted from The Good, the Bad and the Ugly of Private Equity by Sebastien Canderle. source

How can investment professionals improve decision-making in increasingly complex and uncertain markets? In this episode of Conversations with Frank Fabozzi, CFA, Susan Brake offers practical perspectives on the total portfolio approach, governance, and the evolving role of AI in investment decision-making. Key Discussion Points: Rethinking the total portfolio approach Where it works, and where firms get it wrong What actually drives better investment decisions Beyond structure, models, and collaboration Using AI in practice How the role of the investment professional is changing Seeing risk through a systems lens Beyond traditional portfolio models Governance as a performance lever Why decision processes matter more than expected source

We propose a novel method to estimate emotional yields of collectibles based on factor-mimicking portfolios. Using up to 110 years of collectibles returns for 13 distinct asset classes, we apply machine learning techniques to address challenges from non-synchronous trading. We use these estimates to study how emotional yields affect equilibrium pricing. Emotional yield estimates for 24 of our 30 collectibles return series are positive, with an annualized mean (median) of 2.64% (2.53%). Despite various forms of underestimation, these results provide evidence that assets with positive emotional returns have lower equilibrium financial returns. source

Carbon allowance allocation methods in global compliance carbon markets (CCMs) are key market design choices. The allocation of allowances influences the formation of carbon prices, the emission costs for covered entities, and market efficiency. The decision to allocate allowances freely or via auction mechanisms is a critical design feature that affects all stakeholders in the carbon market ecosystem, including covered emitters, market operators, financial intermediaries, and investment firms. In recent years, global CCMs have shifted from free allocation toward auction-based allowance distribution. The calibration of auction mechanisms is a policy choice that plays a critical role in determining market outcomes. This report reviews the auction mechanisms of global CCMs and evaluates their effectiveness, measured by various indicators of market quality. The research is designed to inform the investment industry about various auction mechanisms and to provide practical guidance on participating in auction markets. By reading this report, financial intermediaries and investment firms will be better informed to guide their decisions to participate in the primary market, while policymakers and market operators will be able to determine how best to calibrate allowance allocation in their respective markets. This report is the latest addition to CFA Institute Research and Policy Center’s carbon market research portfolio. Given the global expansion of carbon markets, An Effective Tool for Net Zero and Enhancing the Voluntary Carbon Market: Gaps and Solutions provided detailed overviews of global compliance and voluntary carbon markets, respectively, to help investment industry participants better understand their mechanisms. In light of the rapid growth of carbon-related trading products in secondary markets, Global Compliance Carbon Markets: Structure Explained provided an in-depth analysis of the market structure of global CCMs’ secondary markets, offering practical guidance for the investment industry on engaging with CCMs. Given the significant increase in carbon auction market participation by financial intermediaries and investment firms, as well as the broadened global impact of carbon pricing on firms arising from the EU’s Carbon Border Adjustment Mechanism (CBAM), this report complements previous studies by focusing on the primary markets of global CCMs. The report consists of three main sections: The “Auction Mechanisms” section reviews the auction mechanisms of major CCMs that adopt auctioning. It explains the auction rules, frequency, processes, auction share of allowances, and market development. It covers CCMs in the European Union, New Zealand, California, Quebec, Washington state, and the United Kingdom, analyzing the similarities and unique features of each system. Next, the “Auction Effectiveness” section evaluates the effectiveness of CCM auction mechanisms. It applies three indicators from different dimensions — auction-market price stability (difference between the auction price and prevailing secondary market price, relative to the market price), demand depth (bid-to-cover ratio), and reserve price bindingness (auction clearing price premium) — to assess CCMs in the EU, California, and the United Kingdom. The analysis links these indicators to the specific characteristics of each system. The section “Auction Effectiveness Determinants” explores the key factors that may influence the effectiveness of CCM auctions. Key Findings: The share of allowances auctioned in global CCMs has steadily increased over time. Among CCMs that use auctioning, the primary auction structure is a single-round, sealed-bid, uniform-price auction. To conduct auctions, CCMs use dedicated platforms — the European Energy Exchange (EEX) for the EU, the Western Climate Initiative, Inc. (WCI, Inc.) for California, and the Intercontinental Exchange (ICE) Futures Europe for the United Kingdom. Beyond these similarities, each CCM displays distinct characteristics. The EU Emissions Trading System (EU ETS) has the longest auction history, the largest auction volumes, and the highest frequency (three days per week), making it the most mature auction market. The California Cap-and-Invest Program, formerly the Cap-and-Trade Program, conducts quarterly auctions and uses a relatively strict, annually increasing auction reserve price mechanism that can directly influence auction price levels. The UK Emissions Trading Scheme (UK ETS) holds biweekly auctions. As a newer and smaller CCM, the UK ETS has a tighter auction supply. Investment professionals participating in primary auction markets should be mindful of differences in auction effectiveness across CCMs. As the most mature CCM, the EU ETS has auction clearing prices that are broadly aligned with prevailing secondary market prices. Its auction mechanism demonstrates strong resilience to external shocks and capacity for post-shock self-adjustment. In the long run, the auction mechanism maintains stable, moderate demand depth and a steady auction supply. As a developing CCM, the UK ETS auction tends to clear at a small discount relative to secondary market prices. The alignment between auctions and the secondary market improves over time. The auction mechanism also exhibits stable, moderate demand depth and a steady auction supply. Auction clearing prices are consistently above the constant auction reserve price. As a CCM with a strictly annually increasing auction reserve price and relatively low auction frequency, California’s auction clearing prices are generally aligned with secondary market prices, although occasional large deviations occur because of the strict reserve price policy and the frequency mismatch between auctions and secondary market trading. Demand depth is more volatile, driven by fluctuations on both the demand and supply sides, and oversupply can occur. In most cases, the reserve price is binding; clearing prices are close to it. Auction outcomes are therefore more constrained by reserve prices than driven by market forces. Policymakers and CCM market operators that wish to strengthen the effectiveness of allowance auctions may focus on the efficacy of holding more frequent auctions and increasing the share of allowances auctioned versus free allocation, thereby promoting broader participation in the primary market and enhancing the trading volume and liquidity of allowances in the secondary market. The market design choices discussed in this report can strengthen market functioning by improving transparency, reducing price dispersion and volatility, and stimulating demand. Investment professionals can use this report to guide their participation in global carbon auctions, such as by determining which CCMs to participate in and whether it is profitable to engage in the primary markets. Policymakers can draw on this report’s findings to make targeted improvements to auction mechanisms. source

Understanding the mathematics of loss must ultimately translate into portfolio construction. Not all defensive assets offer the same quality of protection. Conflating perceived safety with genuine downside resilience is a costly mistake. US Treasuries, for example, carry structural, battle-tested protection: deep liquidity, government backing, and a proven track record of holding value during equity drawdowns. Private credit, by contrast, may offer attractive yields but can mask risk through illiquidity and limited price transparency. In periods of severe stress, it may not reprice in the same way as public markets. Instead, liquidity can become constrained. This is a critical distinction. Truly asset-backed investments, where hard collateral such as real property, equipment, or receivables underpins value, provide a more concrete and legally enforceable floor on recovery. Cash flow projections alone are not collateral. *Wealthspring Capital LLC (WSC) is an SEC-registered investment adviser. Registration with the SEC does not imply a certain level of skill or training. Information presented in this article is for educational purposes only and does not constitute individualized investment advice. All investments involve risk, including the possible loss of principal. Past performance is not indicative of future results. source