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Portfolio Management & Construction Flashcards

7 cards from real CFA practice questions. Tap to flip, then mark Knew It or Still Learning — missed cards come back until you master them.

Read the first 7 Portfolio Management & Construction flashcards as text
  1. An investor has a portfolio with expected return of 10% and standard deviation of 15%. The risk-free rate is 3%. What is the Sharpe ratio?

    Answer: 0.47

    Sharpe ratio = (10% - 3%) / 15% = 7/15 ≈ 0.467.

  2. Which of the following best describes the 'core-satellite' portfolio construction approach?

    Answer: A passive index core is supplemented by smaller active or alternative positions

    Core-satellite combines a low-cost passive core (broad market exposure) with satellite positions seeking alpha or diversification.

  3. When constructing a portfolio, the 'information ratio' measures:

    Answer: Active return divided by tracking error

    The information ratio = active return (portfolio return minus benchmark return) divided by tracking error.

  4. A pension fund has a liability duration of 12 years. To implement liability-driven investing (LDI), the fund should:

    Answer: Match the portfolio duration to the liability duration of 12 years

    LDI aims to immunize liability risk by matching the duration of assets to the duration of liabilities.

  5. Which rebalancing strategy involves selling assets that have risen above their target weight and buying those below?

    Answer: Threshold rebalancing

    Threshold (or percentage-of-portfolio) rebalancing triggers trades when any asset class deviates from its target by a set percentage.

  6. In mean-variance optimization, the efficient frontier represents portfolios that:

    Answer: Minimize risk for a given level of expected return

    The efficient frontier consists of portfolios offering the maximum expected return for each level of risk (minimum variance for each return level).

  7. Which of the following is a major limitation of mean-variance optimization in practice?

    Answer: It is highly sensitive to small changes in expected return inputs

    MVO is known for input sensitivity — small changes in expected returns can lead to dramatically different optimal portfolios.