FRM Part 2: Topics Under Risk & Investment Management

Risk Management and Investment Management is one of the six broad topics GARP tests in its FRM Part 2 exam. This broad topic has a 15% weight in the exam. This means out of 80 questions asked, you may expect 12 questions from this section. This area focuses on risk management techniques applied to the investment management process. The broad knowledge points covered in Risk Management and Investment Management include the following:

• Factor theory
• Portfolio construction
• Portfolio risk measures
• Risk budgeting
• Risk monitoring and performance measurement
• Portfolio-based performance analysis
• Hedge funds

There are eleven chapters or readings in this section. If you go through the GARP-specific learning objectives (LOs) for this section, you will find a good mix of computational and non-computational LOs. As GARP generally asks tricky questions from the non-computational LOs, non-computational LOs are equally emphasized to score well in this section.

This article gives you an overview of each of the 11 chapters or readings and identifies the concepts that GARP might test on exam day.

Chapter 1: Factor Theory

This chapter introduces factor theory and factor risk. The vital point is that the exposure to an asset that is compensated is not the exposure to the underlying factors. The risk of these factors is being compensated with risk premiums. The reading mentions different factor theories, including the capital asset pricing model (CAPM) and multifactor models. For the exam, focus on the following:

• Key assumptions of the CAPM while recognizing the model’s limitations in a real-world setting
• Comparison of the CAPM with the assumptions of multifactor models
• Concept of a stochastic discount factor, which is a random variable used in pricing an asset
• The efficient market hypothesis identifies areas of market inefficiencies that can be exploited through active management.

Chapter 2: Factors

Macroeconomic factors are related to asset returns. Economic growth, inflation, and volatility are the most important macro factors that impact returns. Volatility risk can be reduced by investing in low-volatility assets or buying volatility protection in the derivatives market (e.g., buying put options). The capital asset pricing model (CAPM) is a single-factor model that establishes the relationship between asset returns and market risk.

The Fama-French model is a multifactor model that factors in a size factor and a value factor to the original CAPM market factor for explaining stock returns. A momentum factor can also be useful in explaining asset returns. The momentum strategy outperforms the size and value-growth strategy in terms of returns. However, momentum strategies are susceptible to crashes. For the exam, focus on the following:

• Risk and return profiles of each factor
• Rational and behavioural explanations for each factor

Chapter 3: Alpha (and the Low-Risk Anomaly)

Investors are keen on generating alpha, the return earned in excess of a benchmark. It was traditionally thought that higher risk generates higher returns. However, in practice, strategies focused on lower volatility have been found to generate higher returns than higher-volatility investments. For the exam, focus on the following:

• Impact of benchmark section on alpha
• How to apply factor regression to construct a benchmark with multiple factors
• How to measure alpha against that benchmark
• Potential explanations for return anomalies with regard to low risk

Chapter 4: Portfolio Construction

This chapter discusses techniques for optimal portfolio construction and talks about important inputs into the portfolio construction process and means to refine the alpha inputs as an alternative to imposing constraints straight into the portfolio optimization calculations. The role of transaction costs in determining optimal rebalancing is also talked about. For the exam, pay attention to the following:

• Refining alphas and the implications of transaction costs for both rebalancing and dispersion of returns across separately managed portfolios
• Comparison of the various methods of portfolio construction: screening, stratification, linear programming, and quadratic programming

Chapter 5: Portfolio Risk: Analytical Methods

Because of the diversification effect, the value at risk (VaR) of a portfolio will be less than or equal to the sum of the VaRs of the positions in the portfolio. If all positions show perfect correlation, then the portfolio VaR equals the sum of the individual VaRs. A manager can make optimal adjustments to the risk of a portfolio using marginal VaR, incremental VaR, and component VaR. This chapter is highly quantitative. For the exam, pay attention to the following:

• Finding the optimal portfolio using the excess-return-to-marginal VaR ratios
• How correlations impact the measure of portfolio VaR
• How to compute incremental VaR and component VaR using the marginal VaR measure

Chapter 6: VaR and Risk Budgeting in Investment Management

Banks on the “sell side” of the investment industry have been using risk budgeting and value at risk (VaR) for quite some time. The “buy side” investment firms are also increasingly using VaR. One reason for increased use risk budgeting is the increased complexity, dynamics, and globalization of the investment industry. The use of VaR facilitates setting better guidelines as compared to traditional limits. By measuring marginal and incremental VaRs, a manager can make better decisions relating to portfolio weights. For the exam, focus on the following:

• Concept of surplus at risk (SaR)
• How to budget risk across asset classes and active managers

Chapter 7: Risk Monitoring and Performance Measurement

This chapter is primarily qualitative; however, it includes several testable concepts. Many of the concepts discussed here are also discussed in other assigned readings, so this reading should reinforce those concepts. For the exam, focus on the following:

• Three pillars of effective risk management: planning, budgeting, and monitoring
• Concept of a risk management unit (RMU)
• Role of RMU within a company

Chapter 8. Portfolio Performance Evaluation

Professional money managers are continually evaluated using different metrics. In this chapter, alternative methods of computing portfolio returns are discussed. A comparison has been made between time-weighted and dollar-weighted returns for portfolios with cash redemptions and contributions. For the exam, focus on the following:

• Differences in the risk-adjusted performance measures, including the Sharpe ratio, Treynor ratio, Jensen’s alpha, information ratio, and M2
• How the trading practices of hedge funds complicates the evaluation process
• Sharpe’s regression-based style analysis to conduct performance attributions.

Chapter 9. Hedge Funds

The chapter revisits two decades of hedge fund performance. Crucial events that redefined the hedge fund industry are discussed, including the growth of institutional investments. Different hedge fund strategies and the continuing growth of assets under management are also discussed. For the exam, focus on the following:

• Weighing rewards against risks for measuring a manager’s performance
• Benchmarking manager’s performance against broad equity indices
• How to compare the manager’s performance across the hedge fund industry

Chapter 10: Performing Due Diligence on Specific Managers and Funds

This chapter explains why investors should perform due diligence on potential investments. It furnishes a thorough list of items to factor in the due diligence process. For the exam, focus on the steps involved in evaluating a manager, a fund’s risk management process, and a fund’s operational environment.

Chapter 11: Finding Bernie Madoff: Detecting Fraud by Investment Managers

This reading talks about how to predict investment fraud better using publicly disclosed information. Using a panel of mandatory SEC disclosure filings, the authors test the predictability of investment fraud and find that past regulatory and legal violations, conflicts of interest, and monitoring, are significantly related to future fraud. Shunning the 5% of firms with the highest fraud risk lets investors avoid 29% of investment fraud and over 40% of the total dollar losses from fraud.

Even though authors’ predictions are based on publicly available information, they do not find evidence that investors are rewarded for fraud risk through superior performance or lower fees. The results suggest that the currently required disclosures have relevant information, but investors do not fully use this information. Authors recommend changes in SEC disclosure policy that improve investors’ ability to detect fraud at a nominal cost. For the exam, focus on the following:

• Use and efficacy of information disclosures made by investment advisors in predicting fraud
• Barriers and the costs incurred in implementing fraud prediction methods
• Ways to improve investors’ ability to use disclosed data to predict fraud