CFA L3 Trading, Performance Evaluation, and Manager Selection

Pretrade benchmarks

- Decision price. This is the price at the time the portfolio manager made the investment decision. - Previous close. This is the closing price on the previous day (often used as a proxy for decision price by quantitative managers using systematic rules-based, data-driven strategies). - Opening price. This is the opening price on the day (often used as a proxy for decision price for subjective fundamental managers investing in securities for a long-term alpha, since it does not punish or reward traders for news released overnight when markets were closed). - Arrival price. This is the price of the security when the order is sent to the market for execution. Active portfolio managers trying to generate alpha will often specify a benchmark for an arrival price.

Investment Decision-Making Process

- Idea Generation - Idea Implementation - Portfolio Construction - Portfolio Monitoring

Advantages of indirect investments in illiquid assets are:

- Increased diversification across individual projects reduces idiosyncratic risks. It is common to also diversify across project vintage years (the year an investment is first made). - Specialized fund management expertise can be outsourced, so there is no need to recruit, retain, and compensate an internal team. - Liability is limited to only the funds invested.

Disadvantages of indirect investments in illiquid assets are:

- Little control over choice of portfolio assets. - Less information available on individual assets. - Lower portfolio liquidity, as no control over the timing of exits. - Payment of fund management fees, typically 2% annual management and 20% share of profits above a hurdle return. - Uncertain timing of capital calls, which creates liquidity risks.

Disadvantages of direct investments in illiquid assets are:

- Portfolio concentration risk results given the challenge to diversify across enough projects. - Attracting and retaining in-house expertise is challenging and expensive. - Directly owning a business can lead to additional liabilities (e.g., products, customers, legal, health and safety, employee welfare, and environmental). - Being a direct owner increases reputational risk due to being closely associated with a firm should problems occur.

Four key methods to manage liquidity risk include

(1) liquidity profiling and time-to-cash tables, (2) rebalancing and commitments, (3) stress testing, and (4) derivatives

Key factors that dictate the appropriate trading strategy are

(1) order characteristics, (2) security characteristics, (3) market conditions, and (4) individual risk aversion.

Advantages of direct investments in illiquid assets are:

- Control over individual investment assets. - Increased portfolio liquidity due to control over the timing of exits. - Access to more detailed firm information and business plans. - Avoids paying fund management fees (e.g., 2% per annum (pa) and 20% profit sharing over a hurdle return).

tasks performed prior to manager selection:

- Decide that outside support is necessary. - Complete an investment policy statement (IPS). - Determine the appropriate asset allocation..

Execution algorithms

- Scheduled algorithms—percent-of-volume (POV), VWAP, and TWAP algorithms - Liquidity-seeking algorithms (a.k.a. opportunistic algorithms) - Arrival price algorithms - Dark strategies/liquidity aggregators - Smart order routers (SORs)

There are three basic forms of performance-based fees:

- Symmetrical structure with full upside and downside exposures. Fee = base + performance sharing The greatest alignment between investor and manager incentives but increased risk to manager due to the full downside exposure - Bonus with full upside and limited downside exposures. Fee = Greater of: (1) base, (2) base + sharing of positive performance - Bonus with limited upside and downside exposures. Fee = Greater of: (1) base, (2) base + sharing of positive performance (within limit)

Factors that determine the optimal execution approach

- Urgency and size of order. - Liquidity of security (ADV) and the nature of security (e.g., standardized vs. customized). - Characteristics of available execution venues. - Investment strategy objectives (e.g., long term vs. short term in nature). - Reason for the trade.

The three main approaches to conducting performance attribution are returns-based, holdings-based, and transactions-based methods.

1) Returns-based attribution 2) Holdings-based attribution 3) Transactions-based attribution

equitization

In this case, equitization refers to temporarily investing cash using futures or ETFs to gain the desired equity exposure before investing in the underlying securities longer term. Equitization may be required if large inflows into a portfolio are hindered by lack of liquidity in the underlying securities

Liquidity-seeking algorithms

Liquidity-seeking algorithms (a.k.a. opportunistic algorithms) aim to take advantage of favorable liquidity conditions when offered by the market. For example, for a buyer, this algorithm would wait until a large seller appeared and then enter a market order. These orders use both lit and dark venues.

Smart order routers (SORs)

Smart order routers (SORs) are algorithms that determine the best destination (either lit or dark) to route an electronic order to get the best result. SORs focus on getting the best price for market orders, or the highest probability of execution for limit orders.

A five-step liquidity management process is as follows:

Step 1: Establish liquidity risk parameters (policy guidelines, escalation triggers). Step 2: Assess the liquidity of the current portfolio (measure vs. guidelines; monitor). Step 3: Develop a cash flow model (project future expected cash flows). Step 4: Stress test liquidity needs (and cash flow projections). Step 5: Plan for emergencies (a.k.a. a contingency funding plan; what to liquidate, other funding options).

A typical risk management process involves the following steps:

Step 1: Identify risks. Step 2: Measure risks. Step 3: Perform risk mitigation and management. Step 4: Monitor risks. Step 5: Report risks. Step 6: Use analysis and strategic planning.

Automatic adjustment mechanisms

assist in keeping the portfolio risk profile relatively constant if there is a change from the target. For example, assume the portfolio has exposure to market risk relating to private companies and public companies, and that we can use public companies as a proxy for private companies. If the private equity has a beta of 1, and if the private equity allocation falls by 2% relative to the target, then there would be an automatic adjustment to increase the public equity allocation by 2%. That is intended to maintain the level of systematic risk, but of course, it means the level of unsystematic risk (which we can also think of as illiquidity risk) has decreased. The same methodology can be extended to other illiquid asset classes, where the public market can be a reasonable proxy for the private market.

The value of human capital is a function of several factors:

● survival probabilities (usually proxied by mortality tables) ● current employment income ● expected annual wage growth ● the risk-free rate ● a risk adjustment based on occupational income volatility ● the expected number of working years

Asset-Based Benchmarks - Returns-based

Returns-based benchmarks are constructed using (1) the managed account returns over specified periods and (2) corresponding returns on several style indexes for the same periods. Those return series are submitted to an allocation algorithm that solves for the combination of investment-style indexes and most closely tracks the account's returns. Advantages: Generally easy to use and intuitive. Meets the criteria of a valid benchmark. Useful where the only information available is account returns. Disadvantages: The style indexes may not reflect what the manager owns or what the manager or client would be willing to own. Enough monthly returns would be needed to establish a statistically reliable pattern of style exposures. Will not work when applied to managers who change style.

Intraday benchmarks

Volume-weighted average price (VWAP) and Time-weighted average price (TWAP)

Asset-Based Benchmarks - Absolute

Absolute. An absolute benchmark is a return objective that aims to exceed a minimum target return. An example would be the minimum acceptable return (MAR) that is used in computing the Sortino ratio. Advantage: Simple and straightforward benchmark. Disadvantage: Absolute return objective is not an investable benchmark.

alpha decay

Alpha decay is deterioration in alpha once an investment decision has been made. Managers with higher rates of alpha decay (e.g., managers trading on daily news flow) need to trade in shorter time frames; therefore, they have greater trade urgency. Other managers (e.g., managers with insights based on long-term company fundamentals) will have lower rates of alpha decay and therefore a lower trade urgency.

Arrival price algorithms

Arrival price algorithms seek to trade close to market prices prevailing at the time the order is entered. These algorithms will trade more aggressively (i.e., faster) than other algorithms to trade more shares at close to the arrival price.

Asset-Based Benchmarks - Broad market indexes

Broad market indexes. There are several well-known broad market indexes that are used as benchmarks (e.g., S&P 500 for U.S. common stocks). Advantages: Well recognized, easy to understand by clients, and widely available. Unambiguous, generally investable, measurable, and may be specified in advance. Appropriate to use if it reflects the current investment process of the manager. Disadvantage: Manager's style may deviate from the style reflected in the index (e.g., it is not appropriate to use the S&P 500 for a small-capitalization U.S. growth stock manager).

Capture Ratios

Capture ratios determine the manager's relative performance when markets are up or down. Consider an up market where the index or benchmark return is positive. The question is whether the manager's portfolio return is also positive and if it is above or below the benchmark return. For example, if the benchmark return is 4% and the portfolio return is 5%, the upside capture ratio is 125% (5% / 4% = 1.25) and there is outperformance during a period of positive returns. Assuming the same benchmark return but a portfolio return of only 3%, the upside capture ratio is 75% (3% / 4% = 0.75) and there is underperformance during a period of positive returns.

Asset-Based Benchmarks - Custom security-based

Custom security-based benchmarks are designed to reflect the manager's security allocations and investment process. Advantage: Meets all the required benchmark properties and all the benchmark validity criteria. Allows continual monitoring of investment processes. Allows fund sponsors to effectively allocate risk across investment management teams. Disadvantages: It can be expensive to construct and maintain. A lack of transparency by the manager (e.g., hedge funds) can make it impossible to construct such a benchmark.

Enterprise risk management (ERM)

Enterprise risk management (ERM) is a top-down approach in which an organization decides which risks to take and which to avoid or transfer to achieve its purpose and objectives.

Enterprise risk management (ERM)

Enterprise risk management (ERM) is a top-down approach in which an organization decides which risks to take and which to avoid or transfer to achieve its purpose and objectives. ERM typically includes all risks faced by an organization, including major risks such as: Credit risk. Market risk. Operational risk. Liquidity risk. Reputational risk. Environmental, social, and governance risks.

Asset-Based Benchmarks - Factor-model-based

Factor models involve relating a specified set of factor exposures to the returns on an account. A well-known one-factor model (CAPM) is the market model where the return on a portfolio is expressed as a linear function of the return on a market index. Some examples of factors are the market index, industry, growth characteristics, a company's size, and financial strength. The benchmark portfolio (normal portfolio) is the portfolio with exposures to the systematic risk factors that are typical for the investment manager. The manager's past portfolios are used as a guide. Advantages: It is useful in performance evaluation. It provides managers and sponsors with insight into the manager's style by capturing factor exposures that affect an account's performance. Disadvantages: Focusing on factor exposures is not intuitive to all managers or sponsors. The data and modeling are not always available and may be expensive to obtain. It may be ambiguous because different factor models can produce different outputs, leading to misspecification.

HBSA

HBSA looks at the actual securities included in the portfolio at one time. That allows one to estimate the current risk exposures using a more security-specific (bottom-up) approach. Many of the advantages are the same as for RBSA (e.g., determine key risk factors and return drivers, comparability between managers and through time, performed on a timely basis). Overall, HBSA is most appropriate for equity-based strategies.

Which Algorithm?

Liquidity-seeking algorithms are appropriate for larger orders in less liquid markets with higher urgency while trying to mitigate the market impact. They are also appropriate when a manager is concerned that displaying limit orders may lead to information leakage, or when liquidity is typically thin with sporadic episodes of high liquidity. Arrival price algorithms are appropriate for relatively small orders in liquid markets for managers who believe prices are likely to move against them during the trade horizon, and therefore wish to trade more aggressively (e.g., a profit-seeking manager). They are also appropriate for more risk-averse managers who want to minimize execution risk. Dark strategies/liquidity aggregators are appropriate for large orders in illiquid markets, and arrival price or scheduled algorithms would likely lead to high market impact. Since there is a lower chance of execution in dark pools, these strategies are for managers that do not need to execute the full order immediately. SORs are appropriate for small market orders with low market impact where the market can move quickly, or for small limit orders with low information leakage where there are multiple potential execution venues.

Maximum drawdown

Maximum drawdown is the greatest drop in net asset value measured from a high to a low over a specific time period (e.g., the maximum daily drawdown). This is an intuitive risk measure because it is easier to relate to the concepts of declines in value (i.e., drawdowns as opposed to complex calculations).

Micro vs Macro Attribution

Micro attribution analyzes the portfolio at the portfolio manager's level and seeks to verify that the portfolio manager did what they said they would and to understand the drivers of the portfolio's return. Macro attribution analyzes investment decisions at the fund sponsor's level; it's commonly used with institutional investing. Macro attribution quantifies the fund sponsors' decisions to deviate from their strategic asset allocation and the timing when they made those decisions.

Climate risk mitigation and adaption strategies

Mitigation strategies reduce the reliance on fossil fuels and carbon intensive resources. Increases in carbon regulation, restrictions on usage, and carbon taxes will likely increase input costs. Adaption strategies look to prosper in the zero-carbon world, investing in markets, companies, and technologies that are likely to benefit from the transition. Climate change brings many new opportunities aligned to future decarbonization policy and regulation, and it aligns to changing consumer preferences and the opening of new zero-carbon markets, products, and services.

Performance evaluation consists of three interrelated components that build upon each other:

Performance measurement serves as the initial foundation phase and calculates both the return and the risk of the fund over specified time periods. It is imperative to determine, before any performance evaluation analysis, if the portfolio will be compared to a benchmark (relative performance) or to a target return percentage that is specified in advance by the portfolio manager (absolute performance). Performance attribution determines the key drivers that generated the account's performance. Performance attribution expands upon the risk and return that was quantified through performance measurement and explains how the return was achieved given the risk taken by the portfolio manager. Also, performance attribution can explain both relative and absolute returns. Performance appraisal determines whether the performance was affected primarily by investment decisions, by the overall market, or by chance. Performance appraisal combines output from both performance measurement and performance attribution to render a professional judgment on the quality of the performance. If a fund's performance is attributed to luck, we cannot expect the portfolio manager to exhibit similar returns in the future.

Principles for responsible investing (PRI)

Principles for responsible investing (PRI) is a voluntary framework developed in 2006 by the United Nations in collaboration with the investment community, to incorporate ESG issues into investment analysis and decision-making. A key theme of the framework is for investors to be active owners engaging with portfolio firms and seeking ESG disclosures. The aim is to understand current ESG exposures (e.g., carbon dependencies from fossil fuels) and review adaption plans and revised business models for those businesses needing to change to a zero-carbon world.

Asset-Based Benchmarks - Style indexes

Style indexes. Investment-style indexes represent specific portions of an asset category. Four well-known U.S. common stock style indexes are (1) large-capitalization growth, (2) large-capitalization value, (3) small-capitalization growth, and (4) small-capitalization value. Advantages: They are widely available, widely understood by clients, and widely accepted. If the index reflects the manager's style and it is investable, it is an appropriate benchmark. Disadvantages: Some style indexes can contain weightings in certain securities and sectors that may be larger than considered prudent. Differing definitions of investment style can produce quite different benchmark returns, making them inappropriate benchmarks.

liquidity classification schedule (time-to-cash table)

That schedule would have three distinct components: (1) amount of time needed to convert assets to cash, (2) liquidity classification level, and (3) liquidity budget

Sortino Ratio

The Sortino ratio only considers the standard deviation of the downside risk. That is in contrast to the Sharpe ratio, which considers all risk (e.g., both upside and downside). Positive volatility associated with the upside can be considered "good" volatility. The Sortino ratio is more appropriate for investments with non-normal (nonsymmetrical) return distributions. Positively skewed and negatively skewed investment strategies would both result in lower Sharpe ratios (e.g., higher standard deviation in the denominator), but only the negatively skewed investment strategy would result in a lower Sortino ratio (e.g., higher semi-standard deviation in the denominator). Therefore, for investments that have nonsymmetrical or skewed return distributions, such as hedge funds or options, the Sortino ratio appears to be a more appropriate performance metric. However, a comparability problem exists with the Sortino ratio because the determination of MAR is subjective and specific to each investor.

Task Force on Climate-Related Financial Disclosures (TCFD)

The Task Force on Climate-Related Financial Disclosures (TCFD) encourages organizations, including banks, asset managers, and asset owners, to make climate related disclosures within existing reporting requirements. The TCFD, established in 2015, is a voluntary disclosure framework that encourages organizations to make disclosures in the following areas: Governance. Strategy. Risk management. Metrics and targets.

Identify the conditions under which the adviser would find style analysis most useful.

The adviser would find style analysis most useful, whether it be returns based (RBSA) or holdings-based (HBSA), when applied to strategies that hold publicly-traded securities where pricing is frequent. It can be applied to other strategies (hedge funds and private equity, for example), but the insights drawn from a style analysis of such strategies are more likely to be used for designing additional lines of inquiry in the course of due diligence rather than for confirmation of the investment process.

allocation effect

The allocation effect measures the value added/subtracted through the decision to overweight/underweight a segment versus the benchmark. It is calculated by multiplying the active weight in the segment by the passive benchmark segment return. The allocation effect for segment i, Ai, can be formulated as: Ai = (wi - Wi) × Bi

interaction effect

The interaction effect measures the impact on active return of the allocation and selection effects acting together. The interaction effect for segment i, Ii, can be formulated as: Ii = (wi - Wi) × (Ri - Bi)

Quantitative Analysis in manager selection

The manager's performance should be evaluated objectively in terms of the distribution of past returns. Through performance attribution and appraisal, one can distinguish between managerial skills versus luck (e.g., external market factors). The capture ratio would examine performance in both good and weak market conditions. Finally, one must check for any significant drawdowns (i.e., peak-to-trough decline in percentage terms for a specific time period). 1) Attribution and appraisal 2) Drawdown

Asset-Based Benchmarks - Manager universes

The median manager or fund from a broad universe of managers or funds (that follows a similar investment process) is used as the benchmark. The median manager is the fund that falls at the middle when funds are ranked from highest to lowest by performance. Advantage: It is measurable. Disadvantages: Manager universes are subject to "survivor bias," as underperforming managers often go out of business and their performance results are then removed from the universe history. Fund sponsors who choose to employ manager universes must rely on the compiler's representations that the universe has been accurately compiled. They cannot be identified or specified in advance, so it is not investable; thus, it's not an acceptable benchmark.

selection effect

The selection effect measures the value added/subtracted through selecting investments in the portfolio different from those of the benchmark. It is calculated by multiplying the passive benchmark weight of the segment by the active return generated in the segment. The selection effect for segment i, Si, can be formulated as: Si = Wi × (Ri - Bi)

Qualitative Analysis in manager selection

Two important issues arise in qualitative analysis: (1) What is the likelihood that the same level of returns will continue in the future? (2) Does the manager's investment process account for all the relevant risks? 1) Process and People: 2) Operational due diligence

how the performance-based fee structures of the prospective managers may affect portfolio risk

Under the fee structure identified by Porter, Smith's stated expectation would be reflected in a misestimation of portfolio risk because performance-based fee structures may lead to such misestimates. Performance-based fee structures convert symmetrical gross active return distributions into asymmetrical net active return distributions, reducing variability on the upside but not the downside. As a result, a single standard deviation calculated on a return series that incorporates active returns, above and below the base fee, can lead to the underestimation of downside risk. In contrast, fully symmetric fees (fully exposing the manager to both upside and downside results) tend to yield closer alignment in risk and effort than bonus-style fees.

Universal ownership

Universal ownership is a concept that applies to large institutional investors such as pension funds and sovereign wealth funds that create large well-diversified portfolios. The concept of being a universal owner is that, in large portfolios, these investors have their share of both winners and losers from externalities. For example, a portfolio firm that pollutes a river to save costs may well be increasing costs for other firms in the portfolio that rely on the availability of natural resources, such as clean water. The universal owner does not benefit from investing in firms following such practices. Instead, the universal owner benefits from raising ESG standards overall across society.

Risk tolerance is defined within the IPS. Specific risk tolerances can be set for the following:

Volatility. Maximum drawdown. Value at risk and conditional value at risk. Leverage, derivatives, and short positions. Limits on illiquid holdings. Maximum tracking error budgets.

Continuity of returns can be assessed by looking at the four Ps

philosophy, process, people, and portfolio. In short, the philosophy focuses on a specific area of market inefficiency to earn excess returns. Then the process and people will determine whether the strategy is feasible and if it is possible to execute the strategy with the given knowledge and skills of the employees. Finally, the portfolio must be built in a way that is congruent with the philosophy and process.

RBSA

returns-based style analysis (RBSA) RBSA estimates the portfolio's sensitivities to security market indexes for a set of key risk factors. One complication of RBSA is that the risk factors are estimated rather than using predetermined style categories. However, the approach is top-down in nature and little additional data is needed to perform the analysis so the computational approach is relatively easy. RBSA can determine the key risk factors and return drivers for basic and complex strategies. Also, RBSA uses objective data and allows for comparability between managers and through time. Finally, RBSA can be performed on a timely basis (e.g., right after the data is released).