CAIA Level 2 Quiz 105

The question tests the understanding of how futures contracts differ from direct investments in underlying assets, specifically regarding currency risk. While direct investment in foreign equities exposes an investor to both the equity performance and the currency fluctuations of that foreign market, a futures contract on a foreign asset, such as a European equity index, does not carry this direct currency exposure. The contract’s value is tied to the index’s performance, and any gains or losses are settled in cash. The only significant currency exposure for the futures investor arises from the margin posted and any unrealized profits or losses that haven’t been converted back to the investor’s home currency. Therefore, the statement that a long position in a European equity index futures contract has no exposure to the change in the price of the euro is the most accurate representation of this distinction.

The question tests the understanding of how a crack spread hedge functions to lock in a refiner’s margin. In Scenario A, the refiner buys crude oil at $90.06/barrel and sells gasoline at $98.66/barrel and heating oil at $104.24/barrel. The cash market margin is calculated as the weighted average of the output prices minus the input price. For a 3:2:1 spread, this is [(2 * $98.66) + (1 * $104.24) – (3 * $90.06)] / 3 = ($197.32 + $104.24 – $270.18) / 3 = $31.38 / 3 = $10.46 per barrel. The futures market shows the refiner is long crude at $90.06/barrel and short gasoline at $99.16/barrel and heating oil at $104.54/barrel. The futures crack spread is [(2 * $99.16) + (1 * $104.54) – (3 * $90.06)] / 3 = ($198.32 + $104.54 – $270.18) / 3 = $32.68 / 3 = $10.89 per barrel. The net profit/loss from the hedge is the difference between the futures crack spread and the cash market crack spread, adjusted for the difference between the futures and cash prices at the time of the hedge. However, the question asks about the outcome of the hedge in Scenario A. The refiner locked in a margin of $21.88/bbl (from the initial futures calculation). In Scenario A, the cash market margin is $10.46/bbl. The futures market positions offset the adverse movement in cash prices. The refiner bought crude at $90.06 and sold it at $90.06 (futures price). The refiner sold gasoline at $98.66 and bought it back at $99.16 (futures price), resulting in a loss of $0.50/barrel on gasoline. The refiner sold heating oil at $104.24 and bought it back at $104.54 (futures price), resulting in a loss of $0.30/barrel on heating oil. The total loss on the product hedges is (2 * $0.50) + (1 * $0.30) = $1.30 per barrel. The gain on the crude oil hedge is $0.00. The net effect of the futures transactions is a loss of $1.30 per barrel. However, the question asks about the overall outcome of the hedge. The refiner locked in a margin of $21.88/bbl. The cash market margin realized was $10.46/bbl. The difference of $21.88 – $10.46 = $11.42/bbl is the gain from the hedge. This gain offsets the lower-than-expected cash margin. Therefore, the refiner’s effective margin is $10.46 (cash margin) + $11.42 (hedge gain) = $21.88/bbl. The question asks for the outcome of the hedge in Scenario A. The refiner’s initial futures crack spread was $21.88. The cash market margin realized was $10.46. The hedge gain is $21.88 – $10.46 = $11.42. This gain means the refiner’s total profit is $10.46 + $11.42 = $21.88. The question is phrased to test the understanding of how the hedge protects the margin. The refiner’s effective margin is locked in at the initial futures spread, which was $21.88. The futures market transactions resulted in a net gain of $11.42 per barrel ($21.88 initial futures spread – $10.46 realized cash margin). This gain effectively brings the refiner’s total profit up to the initially hedged level.

This question tests the understanding of how currency momentum strategies are implemented and the underlying logic. A momentum strategy involves taking long positions in currencies that have recently appreciated and short positions in currencies that have recently depreciated. The profit or loss is determined by whether this trend continues. If a currency has appreciated (St > St-1), a long position is taken. This position is profitable if the currency continues to appreciate (St+1 > St). Conversely, if a currency has depreciated (St < St-1), a short position is taken, which is profitable if the currency continues to depreciate (St+1 < St). Option B incorrectly suggests that a long position is profitable if the trend reverses, which is the opposite of a momentum strategy. Option C conflates momentum with carry trade logic by referencing interest rate differentials. Option D incorrectly links profit to the absolute change in the spot rate without considering the prior trend and the direction of the trade.

The question tests the understanding of surplus risk in pension plans, which is defined as the tracking error between the plan’s assets and its liabilities. Surplus risk arises from the volatility of both asset returns and liability values, and is exacerbated by a low correlation between them. Exhibit 4.3 illustrates this by showing that even with a negative correlation (-0.26) between assets and liabilities, the volatility of the surplus (17.4%) was higher than the volatility of either assets (11.9%) or liabilities (9.9%). Therefore, a higher surplus risk implies a greater potential for the plan’s assets to deviate from its liabilities, leading to potential underfunding or overfunding issues.

The question tests the understanding of the core mechanics of a carry trade and the conditions under which it remains profitable. A carry trade involves borrowing in a low-interest-rate currency and lending in a high-interest-rate currency without hedging the exchange rate risk. The profit is derived from the interest rate differential. However, this profit can be eroded or reversed if the funding currency appreciates significantly against the target currency. Specifically, the trade remains profitable as long as the depreciation of the target currency (or appreciation of the funding currency) does not exceed the interest rate differential. Option A correctly identifies this critical threshold. Option B is incorrect because while transaction costs are a factor in the overall profitability, they don’t define the point at which the carry trade itself becomes unprofitable due to currency movements. Option C is incorrect as the profitability of the carry trade is directly impacted by the exchange rate movement relative to the interest rate differential, not just the absolute interest rate of the funding currency. Option D is incorrect because while central bank interventions can influence exchange rates, the fundamental condition for carry trade profitability is tied to the exchange rate’s movement relative to the interest rate differential, not the mere existence of interventions.

The regression analysis presented in Exhibit 21.4 indicates that U.S. CPI has a statistically significant positive coefficient (3.203890) and a very low probability (0.0000), signifying that farmland returns act as a strong hedge against inflation. This means that as the general price level rises, the value of farmland tends to increase, preserving the purchasing power of the investment. While industrial production also shows a positive relationship, its coefficient is smaller, and the significance of CPI highlights its primary role as an inflation hedge. Yield to worst, representing interest rates, has a negative coefficient, suggesting that higher interest rates are associated with lower farmland returns, likely due to increased discount rates impacting present values. The U.S. Dollar Index (DXY) also has a positive coefficient, but the CPI’s impact is more directly tied to the concept of inflation hedging.

Gamma measures the rate of change of delta with respect to changes in the underlying stock price. A higher gamma indicates that the delta is more sensitive to stock price movements, necessitating more frequent adjustments to maintain delta neutrality in a convertible arbitrage strategy. Conversely, a lower gamma implies less sensitivity, allowing for less frequent rebalancing. The provided gamma calculation of 0.00794 signifies that for every point change in the underlying stock’s price, the delta is expected to change by 0.00794. This sensitivity is crucial for managing the risk of the equity component of the convertible bond position.

The “entry and establish” phase for both fund managers and investors in private equity is characterized by significant hurdles. For new fund managers, the primary challenge is the lack of a verifiable track record, making it difficult to attract initial capital. This often leads them to adopt specialized or differentiated investment strategies to stand out. Similarly, new investors face an informational disadvantage, struggling to identify and gain access to top-tier fund managers, especially when those managers’ funds are oversubscribed. This initial phase requires both parties to overcome substantial barriers to entry before a stable relationship can be built.

The provided text highlights that while funds of funds (FoFs) offer diversification benefits and lower drawdowns compared to individual hedge funds, this comes at the cost of lower annualized returns. This reduction in returns is attributed to the double layer of fees and potential survivorship bias in single hedge fund performance data. The text explicitly states that FoFs’ average returns are “only a little more than half of those of single hedge funds over the same period.” Therefore, a fiduciary prioritizing capital preservation and downside risk mitigation over maximizing absolute returns would find FoFs more suitable, despite the lower return potential.

The question tests the understanding of how a General Partner’s (GP) personal capital contribution, often referred to as ‘hurt money,’ aligns their incentives with those of the Limited Partners (LPs). A significant personal investment by the GP directly exposes them to potential losses, thereby mitigating the incentive to take on excessive risks. This alignment is crucial because the GP’s compensation structure (carried interest) can otherwise encourage risk-taking to maximize returns, potentially at the expense of the LPs. While management fees are a source of income for the GP, they do not directly link the GP’s personal wealth to the fund’s performance in the same way as a capital contribution. The preferred return is a hurdle for the GP to earn carried interest, and the key-person provision relates to the departure of essential personnel, neither of which directly addresses the GP’s personal financial stake in the fund’s success or failure.

This question tests the understanding of the typical portfolio characteristics of fundamental equity long/short hedge funds. The text explicitly states that these funds are typically highly concentrated, holding a relatively small number of stocks, with core positions ranging from three to ten and non-core positions from twenty to forty. This contrasts with strategies like equity market neutral or statistical arbitrage, which often involve hundreds or thousands of positions. Therefore, a portfolio with a very large number of holdings would be inconsistent with the described characteristics of a fundamental equity long/short strategy.

The provided text highlights that while funds of funds (FoFs) offer diversification benefits and lower drawdowns compared to individual hedge funds, this comes at the cost of lower annualized returns. This reduction in returns is attributed to the double layer of fees and potential survivorship bias in single hedge fund performance reporting. The text explicitly states that FoFs’ average returns are “only a little more than half of those of single hedge funds over the same period.” Therefore, a fiduciary prioritizing capital preservation and downside risk mitigation would likely find FoFs more suitable, despite the lower expected returns.

The question tests the understanding of how different structures for investing in CTAs handle inter-manager risk and performance separation. A Protected Cell Company (PCC) is specifically designed to create legal ‘firewalls’ between different trading entities or accounts within a single overarching structure. This separation prevents the liabilities or performance issues of one cell from impacting another. In contrast, a single SPV with subaccounts (Example 2) lacks these firewalls, allowing for net margining and performance netting across all subaccounts. Therefore, a PCC structure is the most effective for isolating the performance and financial outcomes of individual CTA managers.

The Public Market Equivalent (PME) methodology aims to assess private equity fund performance by simulating an investment in a public market index using the fund’s actual cash flow schedule. By substituting the fund’s Net Asset Value (NAV) with the calculated terminal value from this public market simulation, a private equity equivalent public index Internal Rate of Return (IRR) is derived. This resulting IRR represents the hypothetical performance if the capital had been allocated to the chosen public index instead of the private equity fund, providing a cash-weighted comparison.

Closed-end real estate funds, unlike open-end funds, do not allow for the creation or redemption of shares directly with the fund. This structural difference prevents arbitrageurs from continuously aligning the fund’s market price with its Net Asset Value (NAV). Consequently, closed-end funds, including those focused on real estate, are prone to trading at significant premiums or discounts to their NAVs, particularly when the underlying asset values are not readily observable or are subject to market volatility. This divergence is a key characteristic that distinguishes them from open-end funds and ETFs, which generally maintain a closer correlation between market price and NAV due to their creation/redemption mechanisms.

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 and a negative association with interest rates. It also indicates a positive association with measures of 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 core of unsmoothing a return series relies on accurately estimating the autocorrelation coefficient. The provided text highlights that the success of unsmoothing is highly dependent on the proper specification of the autocorrelation scheme and, crucially, the accurate estimation of its parameters. Equation 16.10 and 16.11 in the material describe how this autocorrelation coefficient (often denoted as \rho or \alpha in similar contexts) is estimated by calculating the correlation between a series and its lagged version. Therefore, a poor estimation of this parameter, as demonstrated in the example with the estimated \rho of 0.037 versus the true \rho of 0.40, directly leads to an inaccurate unsmoothed series. The other options describe potential issues or steps in the process but do not pinpoint the primary reason for the failure of the unsmoothing technique in the given context.

The core issue with appraisal-based real estate indices like NCREIF is that reported returns are smoothed due to the infrequent nature of appraisals. This smoothing artificially reduces the observed volatility and autocorrelation. The unsmoothing process, using a formula like $R_{t,true} = (R_{t,reported} – \rho R_{t-1,reported}) / (1 – \rho)$, where $\rho$ is the autocorrelation coefficient, aims to reveal the underlying, more volatile true returns. A high autocorrelation coefficient (like 83.1% for NCREIF) indicates that past returns have a strong influence on current reported returns, a hallmark of smoothing. When this smoothing is not accounted for, particularly in mean-variance optimization, it leads to a significant underestimation of risk. Consequently, an investor relying on smoothed data would likely overweight such assets, as their perceived risk is lower than their true risk. The REIT index, being market-price-based, exhibits lower autocorrelation and higher observed volatility, reflecting a less smoothed return series.

Limited partners (LPs) often prefer to invest in established fund managers with a proven track record rather than seeking out new, unproven managers. This preference stems from the high costs and time associated with due diligence in the opaque private equity market. Investing with familiar managers reduces these search and evaluation expenses. Furthermore, long-term relationships can grant LPs access to attractive co-investment opportunities and ensure a stable investor base for the fund manager, allowing them to focus on value creation rather than constant fundraising. This predictability in capital commitments also leads to more efficient deployment of capital.

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 as the potential for realizing the value of these options increases. Greater available resources (a larger reserve buffer) also permit more exploration. Finally, a market environment expected to be volatile or disruptive necessitates a broader spread of options (more exploration) to mitigate risk and capture diverse opportunities, whereas a stable environment allows for a reduction in exploration.

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 experimental funds. The satellite portfolio is designed to capture opportunities arising from market shifts or emerging trends, 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 investment time horizon allows for greater exploration because the potential upside from successful bets has more time to materialize. Greater available resources (capital reserves) also permit more exploration, as it provides a buffer against potential losses from the satellite investments. Finally, a market environment expected to be highly volatile or disruptive necessitates a broader range of options (larger satellite allocation) to capture potential opportunities and mitigate risks associated with significant market changes. Conversely, a stable market environment favors a more concentrated core portfolio with reduced exploration.

The payoff-distribution approach to hedge fund replication, as developed by Amin and Kat, focuses on matching the higher moments of the return distribution (such as standard deviation, skewness, and kurtosis) rather than the per-period returns themselves. This is because higher moments are considered more stable and predictable than the mean return, which is highly volatile. The methodology involves dynamic rebalancing, similar to delta hedging an option, where the underlying asset of the option is one of the components. This ensures that the mean return of the replicator is closely aligned with the mean return of the option. However, the primary goal is not to replicate the exact mean return of the hedge fund, but rather to replicate its overall return distribution characteristics. Therefore, while it may not track monthly returns closely, it aims to capture the shape and risk profile of the hedge fund’s returns.

The question tests the understanding of how futures contracts differ from direct investments in underlying assets, specifically regarding currency risk. While direct investment in foreign equities exposes an investor to both the equity performance and the currency fluctuations of that foreign market, a futures contract on a foreign asset, such as a European equity index, does not carry this direct currency exposure. The value of the futures contract itself is denominated in the contract’s currency, and any gains or losses are settled in that currency. The investor’s currency risk is limited to the margin posted and any unrealized profits or losses that have not yet been converted back to their home currency. Therefore, a long position in a European equity index futures contract has minimal exposure to changes in the price of the euro compared to holding the actual European equities.

This question tests the understanding of how global macro funds utilize options trading based on volatility expectations. Managers who are long options benefit from increasing volatility as the probability of significant price movements increases, leading to higher option premiums. Conversely, managers who are short options profit from declining volatility because option premiums tend to decrease. The scenario describes a situation where a manager is short options and aims to profit from time decay, which is most effective when volatility is stable or declining, as the option’s value erodes over time towards expiration. Therefore, expecting declining volatility aligns with the strategy of profiting from time decay when short options.

The question tests the understanding of how equally risk-weighted allocations are constructed. This method involves weighting strategies inversely proportional to their historical standard deviations. The provided data in Exhibit 38.7 shows that the HFRX Merger Arbitrage Index had a significantly lower standard deviation (21.65%) compared to the equally weighted allocation (12.50%), leading to a higher weight in the equally risk-weighted portfolio. Conversely, the HFRX Convertible Arbitrage Index, with a higher standard deviation (6.69% vs. 12.50% equally weighted), would receive a lower weight. The question asks which strategy would receive a *lower* allocation in an equally risk-weighted portfolio compared to an equally weighted one, implying a higher relative volatility. The HFRX Convertible Arbitrage Index, with its higher standard deviation (10.80% in the equally risk-weighted column compared to 12.50% in the equally weighted column), fits this description, indicating it would be down-weighted to compensate for its higher risk. The other options either have lower standard deviations (Merger Arbitrage) or are not as clearly indicated by the data to have significantly higher relative volatility that would lead to a reduced weight in a risk-adjusted framework.

The question tests the understanding of how hedge fund replication strategies are categorized based on their underlying methodology. The provided text indicates that Partners Group’s Alternative Beta Strategies fund, launched in 2004, utilizes a factor-based approach combined with algorithmic execution. This aligns with the description of a factor-based strategy that employs quantitative methods for implementation, as opposed to purely discretionary or simple option replication. The other options represent different methodologies or timeframes not directly associated with the Partners Group fund as described.

The question asks to identify the most appropriate benchmark for a private equity fund’s performance, considering its typical role within an investor’s portfolio. Private equity investments are often made as an alternative to public equity, representing an ‘opportunity cost’ of not investing in public markets. Therefore, comparing a private equity fund’s returns to a public equity index, such as the CAC 40 in the provided example, helps assess whether the illiquidity and higher fees associated with private equity are justified by superior returns. While peer group analysis and absolute return benchmarks are also valuable, the concept of ‘perceived opportunity cost’ directly links the private equity allocation to its public equity alternative, making it a primary consideration for performance evaluation in this context.

The question tests the understanding of how different projection methodologies are applied based on the time horizon and the nature of the information available. Estimates are best suited for short-term horizons (3-6 months) and situations with imperfect data or specific known events, such as upcoming commitments or announced exits. Forecasts rely on trend analysis and expert opinion for medium-term horizons (1-2 years), while scenarios are used for long-term planning (over 2 years) to explore a range of plausible future environments. The scenario described involves assessing the likelihood and size of new commitments within the next few months and anticipating known liquidity events, which aligns perfectly with the characteristics and application of ‘Estimates’.

Convertible arbitrage strategies aim to profit from mispricings in convertible bonds. A common approach involves shorting the underlying stock and buying the convertible bond. This strategy is sensitive to changes in interest rates, which affect the bond’s value. Rho, in the context of the Black-Scholes model, measures the sensitivity of an option’s price to a change in interest rates. For a convertible bond, which has embedded option-like features, an increase in interest rates would generally decrease the value of the fixed-income component, while potentially increasing the value of the conversion option if volatility is high and the bond is deep in the money. However, the primary impact of rising interest rates on the bond’s present value of coupon payments and principal repayment is negative. Therefore, a positive rho for the convertible bond (or the strategy’s net position) would indicate a loss when interest rates rise, and a negative rho would indicate a gain. In a convertible arbitrage strategy where the bond is bought and the stock is shorted, the sensitivity to interest rates is primarily driven by the bond component. An increase in interest rates would decrease the bond’s value, leading to a loss on the long bond position. Thus, the strategy would have a negative sensitivity to interest rate increases, meaning it would have a negative rho.

Limited partners (LPs) in private equity funds face the challenge of monitoring their investments due to the blind-pool nature of these funds and their illiquidity. While LPs cannot easily withdraw commitments like in traditional asset classes, proactive monitoring allows them to identify significant shortcomings early. This early detection can enable the LP to mitigate downside risk by potentially restructuring the investment or exiting the position through the secondary market. The other options describe less direct or less impactful monitoring outcomes. While monitoring can inform decisions about follow-on funds or identify potential spin-outs, its primary role in risk management is to provide avenues for intervention when issues arise.