CFA Level 2 – Portfolio Management – Flashcards
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Mean - variance analysis assumption
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1)All investors are risk averse; they prefer less risk to more for the same level of expected return 2)Expected returns for all assets are known. 3)The variances and covariances of all asset returns are known. 4)Investors need only know the expected returns, variances, and covariances of returns to determine optimal portfolios. They can ignore skewness, kurtosis, and other attributes of a distribution. 5)There are no transaction costs or taxes.
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APT Assumption
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No arbitrage, can diversified all un-systematic risk, many assets available, factor model describe return
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Investment Constraints
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(LLUTT): L (liquidity) - L (legal) - U (unique circumstance) - T (tax) - T (time)
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arbitrage portfolio given expected returns of individual portfolio and their factor sensitivity
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arbitrage portfolio must have zero sensitivity to the factor. so we need to find the weight of each individualmportfolio with the long portfolio weight sum to 1 and the short portfoliomweight sum to -1. the arbitrage profit is weight x expexted return of all portfolio. rêmmber that weight x sensitivity of long port = sensitivity of short port
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factor risk/price of risk
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expected return= risk free+factor sens x price of risk solve this to get price of risk
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liquidity requirements incl what
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does not incl wht is planned
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estimate beta of a stock from its cov with market and mkt variance
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cov with mkt/mkt variance
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std deviation in perfect timing port
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misleading. perfect timing port will perform at least as well of t bills
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TB model result in what kind of port
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result in combination of active port indentified by the model and market (passive) port
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what is CAL
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expected return on how to allocate risky/risky free assets
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what is CML
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when all investors share same expectation, CAL becomes CML
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tracking risk
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sample std deviation x (Return of port - return of benchmark)
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information ratio
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(avg port return - avg benchmark return) / tracking risk
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active risk square
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variance x (port return - benchmark return) active risk square =active factor risk + active specific risk
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FMCAR
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numerator:exposure factor( exposure factor1 x cov1+exposure factor2 x cov2) denominator:active risk square for a single factor: active factor risk/ active rik square
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active factor risk
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(active sensitivity of factor - benchmark) ^2 x factor variance
