Book 5. Risk and Investment Management

FRM Part 2

IM 7. Risk Monitoring and Performance Measurement

Presented by: Sudhanshu

Module 1. Risk Planning, Budgeting and Monitoring

Module 2. Risk Management Units, Liquidity Considerations and Performance Measurement

Module 1. Risk Planning, Budgeting and Monitoring

Topic 1. Three Dimensions of an Effective Risk Management Process

Topic 2. Risk Planning

Topic 3. Risk Budgeting

Topic 4. Risk Monitoring

Topic 1. Three Dimensions of an Effective Risk Management Process

• An effective risk management process has three related fundamental dimensions: risk planning, risk budgeting and risk monitoring.

• Risk Planning: Creates expectations for return and risk (e.g., VaR and tracking error).

• Risk Budgeting: Allocates capital to meet those expectations.

• Risk Monitoring: Identifies any variations from the budget.

• Relation to VaR and Tracking Error: Both VaR and tracking error are measures of risk.
• ​The organization's goal is to maximize profits for a given level of risk taken.

Practice Questions: Q1

Q1. Which of the following statements about tracking error and value at risk (VaR) is least accurate?
A. Tracking error and VaR are complementary measures of risk.
B. Both tracking error and VaR may assume a normal distribution of returns.
C. Tracking error is the standard deviation of the excess of portfolio returns over the return of the peer group.
D. VaR can be defined as the maximum loss over a given period at a given level of confidence.

Practice Questions: Q1 Answer

Explanation: C is correct.

All of the statements are accurate with the exception of the one relating to the peer group. Tracking error is the standard deviation of the excess of portfolio returns over the return of an appropriate benchmark, not peer group.

Topic 2. Risk Planning

• Definition: There are five risk planning objectives for any entity to consider:.

  • Setting Expected Return and Volatility Goals: Specifying acceptable VaR and tracking error. Using scenario analysis for potential failures and responses.

  • Defining Quantitative Measures of Success or Failure: Stating specific guidelines like acceptable Return on Equity (ROE) or Return on Risk Capital (RORC).

  • Generalizing How Risk Capital Will Be Utilized: Defining minimum acceptable RORC for each activity and considering correlations for entity-wide diversification.

  • Defining Difference Between Ordinary vs. Serious Damage: Formulating steps to counter events threatening long-term existence, even if remote. Considering external insurance vs. self-insurance.

  • Identifying Mission Critical Resources: Assessing impact on key employees and financing sources in good and bad times, especially for adverse events occurring together.

• Participants: Requires active input and approval from the entity's owners and highest level of management to ensure risk and return issues are addressed, understood, and communicated.

Topic 3. Risk Budgeting

• Definition: Risk budgeting quantifies the risk plan by allocating risk capital to meet objectives and minimize deviations.

• Process: Structured budgeting process with reasonable return expectations and variability estimates for each allocation.

• VaR in Budgeting: VaR can be calculated for each income statement item, allowing for individual and aggregate RORC calculation.

• Role of Quantitative Methods:

  • Set Minimum Acceptable RORC and ROE: Over various time periods to determine risk-adjusted profitability.

  • Apply Mean-Variance Optimization: Or other quantitative methods to determine asset class weights.

  • Simulate Portfolio Performance: Based on weights and for several time periods, applying sensitivity analysis to changes in return and covariance estimates.

Practice Questions: Q2

Q2. Which of the following statements about the use of quantitative methods in risk budgeting is least accurate? They may be used:
A. to simulate the performance of portfolios.
B. to set levels of return on equity (ROE) and return on risk capital (RORC).
C. in a scenario analysis context to determine the weights for each asset class.
D. in a sensitivity analysis context to consider changes in estimates of returns and covariances.

Practice Questions: Q2 Answer

Explanation: C is correct.

All of the statements are accurate with the exception of the one relating to scenario analysis. One should apply mean-variance optimization (and not scenario analysis) to determine the weights for each asset class.

Topic 4. Risk Monitoring

• Definition: Risk Monitoring seeks and investigates significant variances from the budget within an entity's internal control environment.

• Purpose:

  • Ensure no threats to meeting ROE and RORC targets.

  • Detect and address significant variances in a timely manner.

• Sources of Risk Consciousness (Increasing Awareness):

  • Banks: Concerned with how lent funds are invested.

  • Boards of Investment Clients, Senior Management, Plan Sponsors: More versed in risk management and aware of the need for effective oversight.

  • Investors: More knowledgeable about investment choices (e.g., defined contribution plan beneficiaries selecting investments).

Module 2. Risk Management Units, Liquidity Considerations and Performance Measurement

Topic 1. Risk Management Units (RMU)

Topic 2. Consistency of Investment Activities with Expectations with Risk Monitoring

Topic 3. Liquidity Considerations

Topic 4. Performance Measurement

Topic 5. Comparison of Performance with Expectations

Topic 6. Return Attribution

Topic 7. Sharpe Ratio and Information Ratio

Topic 8. Comparisons With Benchmark Portfolios and Peer Groups

Topic 1. Risk Management Units (RMU)

• A Risk Management Unit (RMU) monitors an investment management entity's portfolio risk exposure and verifies that the exposures are authorized and consistent with the risk budgets that have been previously set. To ensure a proper segregation of duties, the risk management function needs to have an independent reporting line to senior management.

• The objectives of an RMU include:

  • Gathering, monitoring, analyzing, and distributing accurate and relevant risk data to managers, clients, and senior management at the appropriate times.

  • Assisting the entity in formulating a systematic and rigorous method for identifying and dealing with risks, and promoting the entity's risk culture and best risk practices.

  • Taking the initiative to research relevant risk topics that will affect the firm, going beyond merely providing information.

  • Monitoring trends in risk continually and promptly reporting unusual events to management before they become significant problems.

• The objectives of an RMU include (...continued):

  • Promoting discussion throughout the entity and developing a process for discussing and implementing risk data and issues.

  • Promoting a greater sense of risk awareness (culture) within the entity.

  • Ensuring that authorized transactions are consistent with guidance provided to management and with client expectations.

  • Identifying and developing risk measurement and performance attribution analytical tools.

  • Gathering risk data for use in making portfolio manager and market environment assessments.

  • Providing the management team with information to better comprehend risk in individual portfolios as well as the source of performance.

  • Measuring how consistent portfolio managers are with respect to product objectives, management expectations, and client objectives, and bringing significant deviations to the attention of appropriate management for correction.

Topic 1. Risk Management Units (RMU)

Practice Questions: Q1

Q1. A risk management unit (RMU) is most likely to be active in which of the following contexts?
A. Risk monitoring.
B. Risk measurement.
C. Risk budgeting.
D. Risk planning.

Practice Questions: Q1 Answer

Explanation: A is correct.

An RMU monitors an investment management firm’s portfolio risk exposure and ascertains that the exposures are authorized and consistent with the risk budgets previously set.

Topic 2. Consistency of Investment Activities with Expectations with Risk Monitoring

• The RMU confirms consistency of investment activities with expectations using below analysis.

• Forecasting Tracking Error vs. Target: 

  • Consistency Across Portfolios: Tracking error forecast reports should be produced for all accounts managed similarly to gauge the consistency in risk levels taken by the manager.

  • The RMU compares the portfolio manager's forecasted level of tracking error to the established target budget. Predetermined guidelines specify how much variance is acceptable, how much requires further investigation, and how much requires immediate action.

• Risk Capital Allocation: 

  • Overall tracking risk is not sufficient on its own. It is important to break down the tracking risk into "subsections".

  • Detecting Style Drift: If the risk analysis per subsection does not suggest that risk is being incurred in accordance with expectations, it may indicate "style drift". For example, a value portfolio manager might allocate most of the risk to growth investments while still meeting the overall tracking error target.

  • Risk Decomposition: Risk decomposition allows the RMU to verify that portfolio manager activities align with predetermined expectations and stated policies, while detecting unreasonably large risk concentrations at various levels that may jeopardize the portfolio.

Q2. Which of the following statements does not help explain the purpose of risk decomposition?
A. To ensure that there is no style drift.
B. To detect large concentrations of risk.
C. To detect excessive amounts of tracking risk.
D. To ensure that investment activities are consistent with expectations.

Practice Questions: Q2 Answer

Explanation: C is correct.

Risk decomposition is not designed to detect excessive amounts of tracking risk. In fact, it is the forecasted tracking error amount that should be compared to budget to ensure that there is not excessive tracking risk. All the other reasons are consistent with the purpose of risk decomposition.

Topic 3. Liquidity Considerations

• Liquidity considerations are a priority in stress testing because a portfolio's liquidity profile can change significantly during volatile market environments or economic downturns.

• Liquidity Duration: Liquidity duration (LD) is an approximation of the number of days needed to dispose of a portfolio's holdings without causing a significant market impact.

• For a given security, the liquidity duration can be calculated as:

   

​Where:

• $LD=$ liquidity duration for the security (assuming the desired maximum daily volume of any security is 10%)

• $Q=$ number of shares of the security

• $V=$ daily volume of the security

Topic 4. Performance Measurement

• Performance measurement compares a portfolio manager's actual results to relevant comparables like benchmarks and peer groups. The objectives include:

  • Determining whether a manager can consistently outperform (through excess returns) the benchmark or peer group on a risk-adjusted basis.

  • Determining whether the returns achieved are aligned with the risk taken.

  • Identifying managers who are able to generate consistent excess risk-adjusted returns so their superior processes and performance can be replicated to maximize the entity's long-run returns and profitability.

• A performance measurement framework includes:

  • Comparison of performance with expectations.

  • Return attribution.

  • Sharpe ratio and the Information ratio.

  • Comparisons with benchmark portfolios and peer groups.

• From a risk perspective, portfolio managers should be assessed on their ability to produce portfolios with risk characteristics that approximate the target and achieve actual risk levels close to target.
• From a returns perspective, portfolio managers should be evaluated on their ability to generate excess returns above benchmarks.
• Goldman Sachs Asset Management uses a "green zone" system to identify deviations in actual tracking error or performance outside normal expectations, with acceptable statistical deviations considered green zone events.
• "Yellow zone" events represent unusual occurrences expected with some regularity, while "red zone" events indicate truly unusual situations requiring immediate investigation.
• The color-coded system provides clear, predefined expectations for portfolio managers, with movements into yellow or red zones serving as triggers for further investigation and discussion.

Topic 5. Comparison of Performance with Expectations

• The source of returns can be attributed to specific factors or securities.

• It is important to ensure that returns result from decisions where the manager intended to take risk and not simply from sheer luck.

• Variance analysis is used to show the contribution to overall portfolio performance by each security. Securities can be regrouped for analysis by industry, sector, and country.
• Return attribution can employ factor risk analysis and factor attribution, or risk forecasting and attribution at the security level.

Topic 6. Return Attribution

• Sharpe Ratio and Information Ratio: These are both considered risk-adjusted return measures.

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• Strengths of these metrics include:

  • ​Ease of use as a measure of relative performance compared to a benchmark or peer group.

  • Ease of determining if the manager has generated sufficient excess returns in relation to the amount of risk taken.

  • Ease of application to industrial sectors and countries.

• Weaknesses include:

  • Insufficient data may be available to perform calculations.

  • The use of realized risk instead of potential risk may result in overstated performance calculations.

Topic 7. Sharpe Ratio and Information Ratio

Topic 8. Comparisons With Benchmark Portfolios and Peer Groups

• Linear regression analysis can be used to regress the excess returns of the investment against the excess returns of the benchmark or the excess returns of the manager's peer group.

• Regression of investment returns against benchmark returns:

  • Alpha ($\alpha$): Alpha is an output from the regression that can be tested for statistical significance to determine whether the excess returns are attributable to manager skill or just pure luck.
  • Beta ($\beta$): Beta is the other output, which relates to the amount of leverage used or the underweighting/overweighting in the market compared to the benchmark.
  • The regression allows for a comparison of the absolute amount of excess returns compared to the benchmark and the separation of excess returns due to leverage versus those due to skill.
  • Limitation: A limitation is that there may not be enough data available to make a reasonable conclusion as to the manager's skill.
• ​Regression of investment returns against peer group returns:

  • In this regression, the returns of the peer group suffer from survivorship bias, and there is usually a wide range of funds under management among the peers, which reduces comparability.

Practice Questions: Q3

Q3. Which of the following statements regarding alphas and betas is incorrect?
A. Alpha is the excess return attributable to pure luck.
B. Alpha is the excess return attributable to managerial skill.
C. Beta suggests the relative amount of leverage used.
D. Beta suggests whether some of the returns are attributable to over or under weighting the market.

Practice Questions: Q3 Answer

Explanation: A is correct.

Alpha is a measure of the excess return of a manager over the peer group/benchmark that relates to skill as opposed to pure luck. Beta is a measure of the amount of leverage used compared to the peer group or a measure of the underweighting or overweighting of the market compared to the benchmark.