CAIA Level 2 Quiz 89

Global macro managers are characterized by their fundamental analysis, which involves examining economic data, policy decisions, and market sentiment to form investment theses. They are often anticipatory, seeking to identify and capitalize on broad economic trends. In contrast, CTAs (Commodity Trading Advisors) are primarily price-based and follow systematic, momentum-driven strategies, executing trades based on technical signals regardless of underlying fundamentals. While both may participate in established trends, their entry and exit points differ significantly due to their analytical approaches. Feedback-based managers focus on market psychology, information-based managers exploit information gaps, and model-based managers rely on financial models and economic theories. The question asks about the core differentiator between global macro and CTA strategies, which lies in their analytical foundation: fundamentals versus price action.

The passage highlights that while cash and risk-free debt can serve as a straightforward hedge against market downturns, a significant allocation to these assets can diminish the portfolio’s expected long-term return. The text explicitly states that aggressive endowment and foundation investors typically maintain low allocations to these defensive assets, indicating they do not rely on them as a primary tail-risk hedge. Instead, they often utilize alternative investments and options strategies to manage extreme market events.

The question tests the understanding of how combining factors with low correlations can improve a portfolio’s risk-adjusted return. The Fama-French three-factor model (Mkt-RF, SMB, HML) is introduced, and the concept of an equally weighted (EW) portfolio combining these factors is presented. Exhibit 37.3 shows that the EW portfolio has a higher annualized return divided by annualized standard deviation (Ann.Ret/Ann.Std) of 0.61 compared to Mkt-RF (0.28), SMB (0.26), and HML (0.48). This improvement is attributed to the low correlations between the factors, which allow for diversification benefits. Therefore, a quantitative equity strategy that combines factors with low inter-correlations is expected to enhance the overall risk-return profile.

The initial screening phase in private equity fund due diligence is designed to efficiently filter out investment proposals that do not align with the investor’s predefined portfolio objectives and criteria. This includes assessing factors such as industry sector, investment stage, geographical focus, and minimum quality standards. Proposals that fail to meet these initial requirements are immediately disqualified, saving valuable time and resources that would otherwise be spent on more in-depth analysis of unsuitable opportunities. The subsequent stages of due diligence, such as meeting the team and detailed evaluation, are reserved for those proposals that successfully pass this preliminary screening.

This question tests the understanding of how commodity futures are used to hedge against price fluctuations in a producer’s input costs. An airline’s primary fuel cost is jet fuel. Therefore, to hedge against the negative impact of rising jet fuel prices on its profit margins, an airline would benefit from purchasing call options on jet fuel. Call options provide the right, but not the obligation, to buy the underlying asset (jet fuel) at a specified price (the strike price). If jet fuel prices rise significantly above the strike price, the airline can exercise its option to buy jet fuel at the lower strike price, thereby mitigating its increased operating costs. Conversely, buying put options on jet fuel would hedge against a decrease in jet fuel prices, which would be beneficial for a jet fuel producer, not an airline. Selling futures or options would be a speculative strategy or a hedge for a producer, not a consumer facing rising input costs.

This question tests the understanding of how spread trading strategies are initiated and exited based on statistical triggers. The scenario describes a situation where a 100-day statistic for a spread between two commodities has moved to a critical level. A long entry into a spread is triggered when the statistic falls below a negative critical value (e.g., -2.75), indicating the numerator commodity has become relatively cheap. Conversely, a short entry occurs when the statistic rises above a positive critical value (e.g., 2.75), suggesting the numerator has become relatively expensive. Exiting a long spread position happens when the statistic reverts to a level above zero, implying the price ratio has normalized. Similarly, exiting a short spread position occurs when the statistic moves back above zero, indicating the ratio has reverted. Therefore, if the 100-day statistic is currently at 0.5, it signifies that a previously established long spread position (which would have been entered when the statistic was below -2.75) has now crossed the exit threshold of zero, prompting the closure of that long position.

This question assesses the understanding of how non-zero-sum dynamics in futures markets can contribute to returns for trend-following strategies. The core argument presented is that participants with offsetting positions in spot markets may tolerate losses in futures, creating a potential profit source for those who can identify and capitalize on trends. This contrasts with a purely zero-sum view where one party’s gain is precisely another’s loss. Behavioral aspects, such as investor irrationality leading to price trends, are also cited as a source of return, which systematic traders can exploit. Therefore, the ability to profit from market participants willing to accept futures losses due to spot market gains is a key element.

Slate equity financing involves an external investor providing capital for a portfolio of films produced by a studio. This structure is designed to mitigate risk by diversifying investments across multiple projects, adhering to predefined parameters such as risk diversification, release schedules, budget ranges, and genre variety. This approach allows investors to spread their capital across a slate of films, thereby reducing the impact of any single film’s underperformance on the overall investment.

The question probes the understanding of how hedge fund strategy classifications can become blurred over time due to manager behavior. A multistrategy fund that initially focuses on convertible arbitrage might shift its allocations to long/short and event-driven strategies if convertible arbitrage opportunities diminish. The core issue is that data vendors’ classification systems may not always accurately reflect these dynamic shifts in a fund’s underlying strategy composition, potentially leading to misclassification and flawed AUM-based analysis. Therefore, the most accurate statement is that a fund’s classification might not reflect its actual strategy mix if it adapts to changing market conditions.

The question tests the understanding of how different types of inflation impact commodity returns, specifically focusing on the hedging properties. The provided text indicates that unexpected inflation has a significantly larger effect on commodity returns than expected inflation, particularly for storable commodities. The regression analysis in Exhibit 27.4 supports this, showing higher positive coefficients for unexpected inflation (represented by \(\\Delta \text{Inflation}\)) compared to expected inflation (approximated by short-term interest rates). The text explicitly states that the hedging property is much higher when inflation is unexpected. Therefore, an investor seeking to hedge against inflation would find commodities more valuable when inflation surprises the market, as opposed to when it is anticipated.

Convertible arbitrage involves exploiting mispricings in convertible bonds. A common strategy is to short the underlying stock and buy the convertible bond. The goal is to profit from the difference between the bond’s value and the value of the hedged stock position. The “delta hedging” aspect is crucial. Delta represents the sensitivity of the option’s price to a change in the underlying stock price. In convertible arbitrage, the bond’s embedded call option’s delta is used to determine the number of shares to short to hedge the equity risk. If the stock price rises, the value of the call option increases, and the short stock position loses value. The hedge aims to offset this loss. Conversely, if the stock price falls, the call option loses value, and the short stock position gains value. The “gamma” of the option measures the rate of change of delta with respect to the stock price. A positive gamma means that as the stock price increases, the delta of the call option also increases, requiring the arbitrageur to buy back more stock to maintain the hedge. Conversely, as the stock price falls, the delta decreases, requiring the arbitrageur to sell more stock. This dynamic adjustment process is known as gamma hedging. Therefore, a convertible arbitrageur would be concerned about positive gamma because it implies that the hedge needs to be adjusted more frequently and potentially at less favorable prices as the stock price moves, increasing transaction costs and the risk of hedge slippage.

This question tests the understanding of the relationship between farmland returns and macroeconomic factors. The provided text explicitly states that factor modeling of U.S. farmland shows a positive correlation with U.S. inflation, indicating it acts as a real asset. It also shows a negative association with interest rates and a positive association with economic growth. Therefore, an increase in inflation and economic growth, coupled with a decrease in interest rates, would generally lead to higher farmland returns. Option A correctly reflects this relationship.

The endowment model, as discussed in the provided text, emphasizes superior manager selection as a primary driver of outperformance, particularly within alternative asset classes. While strategic asset allocation is important, research indicates that differences in manager selection explain a significantly larger portion of return variations across endowments compared to asset allocation or market timing. The text highlights that top endowments outperform smaller ones across most asset classes, with the margin widening in alternatives like private equity and natural resources, directly attributable to the skill of the selected managers.

This question tests the understanding of how spread trading strategies are initiated and exited based on statistical triggers. The scenario describes a situation where a 100-day statistic for a spread between two commodities (implied by the price ratio) is used to determine trading actions. A long entry into the spread is triggered when the statistic falls below a critical negative value (-2.75 in the example), indicating the denominator commodity has become relatively too expensive. Conversely, a short entry occurs when the statistic rises above a positive critical value (2.75). Exiting a long spread position happens when the statistic reverts to a level above zero, suggesting the price ratio has normalized. Similarly, exiting a short spread position occurs when the statistic moves back above zero, indicating the numerator commodity is no longer excessively expensive relative to the denominator. Therefore, a long spread position is closed when the statistic moves from a negative value towards zero, specifically crossing above it.

The question tests the understanding of the inherent risks associated with short selling in the context of a long/short equity hedge fund strategy. The provided text highlights that short selling is generally considered riskier than buying stocks due to several factors. These include the potential for unlimited losses (as a stock price can theoretically rise indefinitely), the requirement to borrow stock which can lead to forced covering (e.g., if the lender sells the stock), and the risk of short squeezes where coordinated buying pressure can rapidly drive up the stock price, forcing short sellers to cover at unfavorable prices. While regulatory actions can impact short selling, and market impact can be larger during execution, the fundamental asymmetry of potential losses and the mechanics of borrowing and covering are the primary drivers of increased risk compared to long positions. Therefore, the most accurate statement is that short selling carries a higher inherent risk due to the potential for unlimited losses and the mechanics of borrowing and covering.

Convertible arbitrage strategies, particularly those involving delta hedging, are sensitive to the frequency of rebalancing. Continuous delta hedging, while theoretically ideal, is impractical due to transaction costs and the discrete nature of price movements and trading. In practice, arbitrageurs rehedge at discrete intervals, either based on time (e.g., daily) or price movements (e.g., a $1 change). The core concept is that a smaller rebalancing interval reduces the risk of being poorly hedged. If the interval is too large, the position’s delta can deviate significantly from zero, exposing the arbitrageur to market risk. Therefore, a smaller rebalancing interval is generally preferred to maintain a more accurate hedge, despite the increased transaction costs. The question tests the understanding of the trade-off between hedging accuracy and transaction costs in a practical convertible arbitrage setting.

The question tests the understanding of commodity futures’ diversification benefits over different holding periods. Research, such as that by Gorton and Rouwenhorst (2006), indicates that while the correlation between commodity futures and stocks might be near zero at very short horizons, this correlation tends to become more negative as the holding period increases. This negative correlation is the primary driver of diversification benefits, as it implies that commodity futures can offset losses in equity and bond portfolios during certain market conditions, particularly over longer investment horizons. Therefore, the diversification advantage is more pronounced as the investment duration lengthens.

The Financial Services and Markets Act 2000 (FSMA) in the UK, similar to regulations in other jurisdictions, imposes requirements on firms managing collective investment schemes, including hedge funds. One key aspect is the need for authorization from the relevant regulatory body, which in the UK was the Financial Services Authority (FSA) at the time of the text. This authorization process involves multiple steps, including the submission of detailed applications for both the firm and key personnel, demonstrating financial soundness, and undergoing interviews. The FSMA also governs the marketing of these schemes, setting parameters akin to those found in the US regarding investor numbers and advertising restrictions. The Public Offers of Securities Regulations 1995 (POS Regulations) further detail the structural aspects of private placements for hedge funds. Therefore, a hedge fund manager operating in the UK would need to comply with these regulatory frameworks to conduct business legally.

The core-satellite portfolio approach in private equity involves allocating capital to a ‘core’ portfolio of established, lower-risk funds and a ‘satellite’ portfolio of newer, higher-risk, or opportunistic funds. The satellite portfolio is designed to capture potential upside from market shifts or emerging opportunities, acting as a form of ‘real option’. The decision to allocate more to the satellite portfolio (exploration) versus the core portfolio (exploitation) is influenced by several factors. A longer time horizon allows for greater exploration because the potential for future value realization from these options increases. Similarly, greater available resources (a larger reserve buffer) permit more exploration, as it can absorb potential initial losses from these riskier bets. Finally, a market environment expected to be volatile or disruptive necessitates a broader spread of options (more exploration) to capture potential upside and mitigate unforeseen risks, whereas a stable environment favors a more concentrated, exploitation-focused approach.

The core of effective risk management in hedge funds and funds of funds, as highlighted by Halpern and Liew, lies in its ‘actionability.’ This means the risk management function must have the explicit authority and demonstrated willingness to reduce risk, even if it means cutting profitable positions or strategies. The ability to enforce risk limits, regardless of the portfolio manager’s popularity or the profitability of a given strategy, is paramount. While understanding a fund’s risk characteristics through reports and quantitative measures like VaR is important, it’s secondary to the practical implementation of risk reduction. Fraud prevention is a separate, albeit crucial, concern, and hidden risks require specific analytical techniques beyond standard correlation analysis.

The provided exhibit demonstrates that while short-term correlations between commodity returns and inflation can be volatile and sometimes negative, longer-term averages reveal a more consistent positive relationship, particularly for energy and industrial metals with US inflation, and agriculture with European and Asian inflation. The text explicitly states that over longer periods (three and five years), correlations become stronger and more stable, suggesting that commodities, especially certain categories, can serve as inflation hedges. The question tests the understanding of this time-horizon dependency and the nuanced relationship between different commodity types and regional inflation, as depicted in the exhibit.

Managed accounts offer investors direct control over their assets and the ability to liquidate positions at any time, thereby avoiding the typical lock-up periods associated with pooled investment vehicles like hedge funds. This enhanced liquidity and direct oversight are key advantages. While transparency is a benefit, it’s a consequence of direct control rather than the primary structural advantage. The reduced pool of managers and administrative responsibilities are drawbacks, not primary benefits. The ability to choose leverage parameters is a feature that enhances control, but the fundamental advantage is the direct control and liquidity.

The endowment model, as discussed in the context of institutional investing, emphasizes a strategic asset allocation approach. While studies on pension plans historically attributed a significant majority of return variance to strategic asset allocation (91.5%-93.6%), research on endowments, such as that by Brown, Garlappi, and Tiu (2010), indicated a more substantial contribution from dynamic asset allocation and manager selection. Specifically, this research found that strategic asset allocation explained a smaller portion of returns (74.2%), with market timing contributing 14.6% and security selection 8.4%. This suggests that while strategic allocation is foundational, the endowment model’s success is more deeply rooted in active management decisions and the selection of skilled managers, particularly within alternative asset classes where return dispersion is often wider. The question tests the understanding of how the drivers of return attribution differ between traditional pension plans and the endowment model, highlighting the increased importance of active management and manager selection in the latter.

The scenario describes a situation where a country’s central bank is forced to defend a fixed exchange rate band. To do this, it must intervene in the foreign exchange market by selling its foreign currency reserves and buying its own currency. If speculative pressure is intense and sustained, the central bank’s reserves can be depleted. In such a situation, to further support the currency and make it more expensive for speculators to maintain short positions, the central bank might be compelled to raise its domestic interest rates. This increases the cost of borrowing the domestic currency for speculative selling and makes holding the currency more attractive due to higher returns. The text explicitly mentions the Bank of England raising its base lending rate in response to speculative pressure on the pound.

The core challenge with non-investable hedge fund indices is the difficulty in replicating their performance due to several factors. These include a lack of transparency regarding components and methodologies, the presence of closed or capacity-constrained funds, illiquidity issues preventing traditional indexing techniques, and significant time lags in reporting Net Asset Values (NAVs). These combined issues make it impractical for a third-party indexer to accurately track and replicate such indices. Investable indices attempt to overcome these hurdles by selecting a limited number of liquid and open funds, but this selection process itself can introduce access bias, potentially leading to lower returns compared to the broader universe.

Convertible arbitrage strategies aim to profit from mispricings between a convertible bond and its underlying equity. A key component of this strategy involves hedging the equity exposure. Delta hedging is a common technique where the hedge fund manager adjusts the short position in the underlying stock to offset the sensitivity of the convertible bond’s option component to changes in the stock price. This process is dynamic, as the delta changes with the stock price and time to expiration. The goal is to maintain a delta-neutral position, thereby isolating the arbitrage opportunity from directional equity market movements. While other hedges might be employed (like hedging interest rate or credit risk), delta hedging is the primary method for managing the equity component’s price sensitivity.

The question tests the understanding of how exchange rate movements impact commodity prices, particularly those denominated in U.S. dollars. When the U.S. dollar depreciates, foreign buyers of dollar-denominated commodities need to pay more in their local currency to acquire the same amount of the commodity. To maintain their purchasing power and profitability, commodity exporters will then demand a higher dollar price for their goods. Conversely, an appreciating dollar makes commodities cheaper for foreign buyers, potentially leading to lower dollar-denominated prices. The scenario highlights that while a depreciating dollar generally increases dollar-denominated commodity prices, the specific case of South African gold in 2001, where the rand depreciated but the dollar gold price fell, illustrates that other factors, such as changes in demand or supply responses (like increased production due to higher local currency profits), can influence this relationship.

The question tests the understanding of how intellectual property (IP) is valued and the inherent risks associated with early-stage IP investments. Newly created IP, such as exploratory research or pending patents, is characterized by significant uncertainty regarding its future value and utility. This uncertainty is akin to venture capital investments, where a large proportion may not recoup initial costs, but a small fraction can generate substantial returns. Mature IP, on the other hand, has established utility and a more predictable income stream, leading to more certain valuations and market pricing that reflects known risks. Therefore, the most accurate description of newly created IP from an investment perspective is its high degree of uncertainty and potential for both significant loss and outsized gains.

Funds of Hedge Funds (FoFs) offer diversification and professional management, but investors surrender direct control over underlying investments. This lack of direct control means investors cannot tailor specific allocations to their unique needs, such as avoiding certain asset classes due to sponsor business risks. While FoFs aim to add value through strategic and tactical asset allocation and manager selection, the inherent structure limits an individual investor’s ability to customize their exposure, a benefit available through direct investment in individual hedge funds.

Hedonic price indices estimate the value of properties that have not recently traded by modeling property value as a function of specific characteristics. This involves fitting parameters to a valuation model using data from recent transactions and then applying these estimated parameters to infer the values of properties that did not transact. This approach directly addresses property heterogeneity, unlike repeat-sales indices which focus on price changes of properties that have transacted multiple times. Market-traded vehicles like REITs are a separate category based on the prices of securities, not direct property valuations.