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Equity Portfolio Management: Active or Passive?. Passive: LT buy and hold Indexation Replication of an index (broad or specialized Sampling and Tracking Error  = 0 Rebalancing. Equity Portfolio Management: Active or Passive?. Rebalancing an Equity Portfolio. Why?

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equity portfolio management active or passive
Equity Portfolio Management: Active or Passive?
  • Passive:
    • LT buy and hold
    • Indexation
      • Replication of an index (broad or specialized
      • Sampling and Tracking Error
      •  = 0
    • Rebalancing
rebalancing an equity portfolio
Rebalancing an Equity Portfolio
  • Why?
    • to manage tracking error (if indexing or not)
    • to maintain a desired set of weights or risk level
    • client needs change
    • Market risk level changes
    • bankruptcies, mergers, IPOs
  • Why not?
    • it’s costly!
rebalancing example 16
Rebalancing: Example 1
  • Portfolio is no longer equally weighted
  • To rebalance:
    • Sell Y, buy X and Z
    • Positions must be reset to $10445/3 = $3482
    • Sell 4440 - 3482 = $958 of Y (48 shares)
    • Buy 3482 - 2672 = $810 of X (51 shares)
    • Buy 3482 - 3325 = $157 of Z (4 shares)
rebalancing example 18
Rebalancing: Example 1
  • LT effects of this strategy?
  • Alternatives?
  • Example 2: Rebalancing to reestablish a specific level of systematic risk (Target Beta = 1.2)
rebalancing example 2
Rebalancing: Example 2
  • Reestablishing a beta of 1.2:
    • No unique solution for more than 2 securities
    • Need to sell high  stocks and buy low  stocks
    • For example, sell Y, buy Z, hold X constant
    • p = (.256)(1.3)+(WY)(1.7)+(1-.256-WY)(.8)
    • Find Y such that p = 1.2
      • WY = .302 => WZ = 1-.256-.302 = .442
      • $3488 in X, $3151 in Y, $4611 in Z
active equity strategies
Active Equity Strategies
  • Beat the market on a risk adjusted basis!
  • Need a benchmark
  • More expensive: turnover, research
  • Must outperform on a fee-adjusted basis
active equity strategies11
Active Equity Strategies
  • Styles:
    • Sector Rotation: move in/out of sectors as economy improves/declines
    • Earnings Momentum: overweight stocks displaying above average earnings growth
    • Enhanced Index Fund - majority of funds track index, some funds are actively managed
    • Quantitative Investment Management
quantitative investment management
Quantitative Investment Management
  • How do we forecast performance ?
    • Screening (Fundamental or Technical factors)
    • Rank based on some set of factors that correlates with future performance (such as regression analysis)
  • How do we improve forecasting model?
    • Add more data (more observations)
    • Uncover new causal relationships (variables)
quantitative investment management13
Quantitative Investment Management
  • Regardless of forecast, there are three basic results common to QIM:
    • 1. Information comes from unexpected events
      • events with low probability have high info content!
slide14
QIM
  • 2. Profitable QIM techniques won’t be commercialized
    • Starting with a multifactor model:
    • Ri = b1F1 + b2F2 + . . . + bkFk + ei
    • It isn’t easy to get information from these residuals:
      • 1. patterns are complex
      • 2. quality of data is limited
      • 3. outliers may draw undue attention (although irrelevant)
      • 4. human judgement is superior
      • 5. analysis must be flexible (more data, constraints)
      • 6. danger of data mining
      • 7. even if significant, outliers are too few in number!
slide15
QIM
  • 3. Non-linear models are important
    • Neural Networks
    • Genetic Algorithms
    • Fuzzy Logic
    • Non-Linear Dynamics
    • Classification Trees (Recursive Partitioning)