Portfolio Management Flashcards
Explain the creation/redemption process of ETFs and the function of authorized participants.
Authorized participants (APs) can create additional shares by delivering the creation basket to the ETF manager. Redemption is similarly conducted by tendering ETF shares and receiving a redemption basket. These primary market transactions are in kind and require a service fee payable to the ETF issuer, shielding the nontransacting shareholders from the costs and tax consequences of creation/redemption. The creation/redemption process ensures that market prices of ETFs stay within a narrow band of the NAV.
Describe how ETFs are traded in secondary markets.
ETFs are traded just like other shares on the secondary markets. Market fragmentation may widen the quoted spreads for European ETFs.
Describe sources of tracking error for ETFs.
Tracking error is the annualized standard deviation of the daily tracking difference. Sources of tracking error include fees and expenses of the fund, sampling, and optimization used by the fund, the fund’s investment in depository receipts (DRs) (as opposed to the underlying shares directly), changes in the index, regulatory and tax requirements, fund accounting practices, and asset manager operations.
Describe factors affecting ETF bid–ask spreads.
ETF spreads are positively related to the cost of creation/redemption, the spread on the underlying securities, the risk premium for carrying trades until close of trade, and the APs’ normal profit margin. ETF spreads are negatively related to the probability of completing an offsetting trade on the secondary market. Creation/redemption fees and other trading costs can influence spreads as well.
Describe sources of ETF premiums and discounts to NAV.
ETF premium (discount) % = (ETF price – NAV) / NAV
Sources of premium or discount include timing difference for ETFs with foreign securities traded in different time zones and stale pricing for infrequently traded ETFs.
Describe costs of owning an ETF.
ETF costs include trading cost and management fees. Short-term investors focus on lower trading costs while longer-term, buy-and-hold investors seek lower management fees. Trading costs tend to be lower for more-liquid ETFs. Liquidity is evaluated using the ratio of average dollar volume to average assets (higher is better).
Describe types of ETF risk.
Risks of investing in ETFs include counterparty risk (common for ETNs), fund closures, and expectation-related risk.
Identify and describe portfolio uses of ETFs.
Portfolio uses of ETFs include the following:
- Efficient portfolio management, including liquidity management, portfolio rebalancing, portfolio completion, and transition management.
- Asset class exposure management, including core exposure to an asset class or sub-asset class as well as tactical strategies.
- Active investing, including smart beta, risk management, alternatively weighted ETFs, discretionary active ETFs, and dynamic asset allocation.
Describe arbitrage pricing theory (APT), including its underlying assumptions and its relation to multifactor models.
The arbitrage pricing theory (APT) describes the equilibrium relationship between expected returns for well-diversified portfolios and their multiple sources of systematic risk. The APT makes only three key assumptions: (1) unsystematic risk can be diversified away in a portfolio, (2) returns are generated using a factor model, and (3) no arbitrage opportunities exist.
Define arbitrage opportunity and determine whether an arbitrage opportunity exists.
An arbitrage opportunity is defined as an investment opportunity that bears no risk and has no cost, but provides a profit. Arbitrage is conducted by forming long and short portfolios; the proceeds of the short sale are used to purchase the long portfolio. Additionally, the factor sensitivities (betas) of the long and short portfolios are identical and, hence, our net exposure to systematic risk is zero. The difference in returns on the long and short portfolios is the arbitrage return.
Describe and compare macroeconomic factor models, fundamental factor models, and statistical factor models.
A multifactor model is an extension of the one-factor market model; in a multifactor model, asset returns are a function of more than one factor. There are three types of multifactor models:
Macroeconomic factor models assume that asset returns are explained by surprises (or shocks) in macroeconomic risk factors (e.g., GDP, interest rates, and inflation). Factor surprises are defined as the difference between the realized value of the factor and its consensus expected value.
Fundamental factor models assume asset returns are explained by the returns from multiple firm-specific factors (e.g., P/E ratio, market cap, leverage ratio, and earnings growth rate).
Statistical factor models use multivariate statistics (factor analysis or principal components) to identify statistical factors that explain the covariation among asset returns. The major weakness is that the statistical factors may not lend themselves well to economic interpretation.
Explain sources of active risk and interpret tracking risk and the information ratio.
Active return is the difference between portfolio and benchmark returns (RP − RB), and active risk is the standard deviation of active return over time. Active risk is determined by the manager’s active factor tilt and active asset selection decisions:
active risk squared = active factor risk + active specific risk
The information ratio is active return divided by active risk
Describe uses of multifactor models and interpret the output of analyses based on multifactor models.
Multifactor models can be useful for risk and return attribution and for portfolio composition. In return attribution, the difference between an active portfolio’s return and the benchmark return is allocated between factor return and security selection return.
In risk attribution, the sum of the active factor risk and active specific risk is equal to active risk squared (which is the variance of active returns):
active risk squared = active factor risk + active specific risk
active factor risk = active risk squared − active specific risk
Multifactor models can also be useful for portfolio construction. Passive managers can invest in a tracking portfolio, while active managers can go long or short factor portfolios.
A factor portfolio is a portfolio with a factor sensitivity of 1 to a particular factor and zero to all other factors. It represents a pure bet on a single factor and can be used for speculation or hedging purposes. A tracking portfolio is a portfolio with a specific set of factor sensitivities. Tracking portfolios are often designed to replicate the factor exposures of a benchmark index like the S&P 500.
Describe the potential benefits for investors in considering multiple risk dimensions when modeling asset returns.
Multifactor models enable investors to take on risks that the investor has a comparative advantage in bearing and avoid the risks that the investor is unable to absorb.
Models that incorporate multiple sources of systematic risk have been found to explain asset returns more effectively than single-factor CAPM.
Explain the use of value at risk (VaR) in measuring portfolio risk.
Value at risk (VaR) is an estimate of the minimum loss that will occur with a given probability over a specified period expressed as a currency amount or as percentage of portfolio value.
Calculate the expected return on an asset given an asset’s factor sensitivities and the factor risk premiums.
Expected return = risk-free rate + ∑(factor sensitivity) × (factor risk premium)
Compare the parametric (variance–covariance), historical simulation, and Monte Carlo simulation methods for estimating VaR.
Value at risk estimation methods:
Parametric method—uses the estimated variances and covariances of portfolio securities to estimate the distribution of possible portfolio values, often assuming a normal distribution.
Historical simulation—uses historical values for risk factors over some prior lookback period to get a distribution of possible values.
Monte Carlo simulation—draws each risk factor change from an assumed distribution and calculates portfolio values based on a set of changes in risk factors; repeated thousands of times to get a distribution of possible portfolio values.
Estimate and interpret VaR under the parametric, historical simulation, and Monte Carlo simulation methods.
The x% VaR is calculated as the minimum loss for the current portfolio, x% of the time, based on an estimated distribution of portfolio values.
Describe advantages and limitations of VaR.
Advantages of VaR:
Widely accepted by regulators.
Simple to understand.
Expresses risk as a single number.
Useful for comparing the risk of portfolios, portfolio components, and business units.
Disadvantages of VaR:
Subjective in that the time period and the probability are chosen by the user.
Very sensitive to the estimation method and assumptions employed by the user.
Focused only on left-tail outcomes.
Vulnerable to misspecification by the user.
Describe extensions of VaR.
Conditional VaR (CVaR) is the expected loss given that the loss exceeds the VaR. Sometimes referred to as the expected tail loss or expected shortfall.
Incremental VaR (IVaR) is the estimated change in VaR from a specific change in the size of a portfolio position.
Marginal VaR (MVaR) is the estimate of the change in VaR for a small change in a portfolio position and is used as an estimate of the position’s contribution to overall VaR.
Ex ante tracking error, also referred to as relative VaR, measures the VaR of the difference between the return on a portfolio and the return on the manager’s benchmark portfolio.
Describe sensitivity risk measures and scenario risk measures and compare these measures to VaR.
Sensitivity analysis is used to estimate the change in a security or portfolio value to an incremental change in a risk factor.
Scenario analysis refers to estimation of the effect on portfolio value of a specific set of changes in relevant risk factors.
A scenario of changes in risk factors can be historical, based on a past set of risk factors changes that actually occurred, or hypothetical (based on a selected set of significant changes in the risk factors of interest).
Demonstrate how equity, fixed-income, and options exposure measures may be used in measuring and managing market risk and volatility risk.
Equity risk is measured by beta (sensitivity to overall market returns).
The interest rate risk of fixed-income securities is measured by duration (sensitivity to change in yield) and convexity (second-order effect, change in duration).
Options risk is measured by delta (sensitivity to asset price changes), gamma (second-order effect, change in delta), and vega (sensitivity to asset price volatility).
Market risk can be managed by adjusting portfolio holdings to control the exposures to these various risk factors.
Describe the use of sensitivity risk measures and scenario risk measures.
A stress test based on either sensitivity or scenario analysis uses extreme changes to examine the expected effects on a portfolio or organization, often to determine the effects on a firm’s equity or solvency. A reverse stress test is designed to identify scenarios that would result in business failure.
Sensitivity analysis can give a risk manager a more complete view of the vulnerability of a portfolio to a variety of risk factors. Sensitivity and scenario risk measures provide additional information about portfolio risk but do not necessarily provide probabilities or, in the case of sensitivity measures, the sizes of expected changes in risk factors and portfolio value.
Sensitivity and scenario analysis provide information that VaR does not and are not necessarily based on historical results. A historical scenario will not necessarily be repeated. Hypothetical scenarios may be misspecified, and the probability that a scenario will occur is unknown.
Describe advantages and limitations of sensitivity risk measures and scenario risk measures.
VaR, sensitivity analysis, and scenario analysis complement each other, and a risk manager should not rely on only one of these measures.
VaR provides a probability of loss.
Sensitivity analysis provides estimates of the relative exposures to different risk factors, but does not provide estimates of the probability of any specific movement in risk factors.
Scenario analysis provides information about exposure to simultaneous changes in several risk factors or changes in risk correlations, but there is no probability associated with a specific scenario.
Explain constraints used in managing market risks, including risk budgeting, position limits, scenario limits, and stop-loss limits.
Risk budgeting begins with determination of an acceptable amount of risk and then allocates this risk among investment positions to generate maximum returns for the risk taken.
Position limits are maximum currency amounts or portfolio percentages allowed for individual securities, securities of a single issuer, or classes of securities, based on their risk factor exposures.
A stop-loss limit requires that an investment position be reduced (by sale or hedging) or closed out when losses exceed a given amount over a specified time period.
A scenario limit requires adjustment of the portfolio so that the expected loss from a given scenario will not exceed a specified amount.
Explain how risk measures may be used in capital allocation decisions.
Firms use risk measures by adjusting expected returns for risk when making capital allocation decisions.
Describe risk measures used by banks, asset managers, pension funds, and insurers.
Banks are concerned with many risks including asset-liability mismatches, market risk for their investment portfolio, their leverage, the duration and convexity of their portfolio of fixed-income securities, and the overall risk to their economic capital.
Asset managers are most concerned with returns volatility and the probability distribution of either absolute losses or losses relative to a benchmark portfolio.
Pension fund managers are concerned with any mismatch between assets and liabilities as well as with the volatility of the surplus (assets minus liabilities).
P&C companies are concerned with the sensitivity of their investment portfolio to risk factors, the VaR of their economic capital, and scenarios that incorporate both market and insurance risks as stress tests of the firm.
Life insurers are concerned with market risks to their investment portfolio assets and liabilities (to make annuity payments), any mismatch between assets and liabilities, and scenarios that would lead to large decreases in their surplus.
