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Dynamic vs static asset allocation
 Dynamic: risk and return in one period affects performance in subsequent periods; difficult and costly; preferred for ALM
 Static: ignores correlation among periods

Behavioral biases associated with asset allocation
 loss aversion
 mental accounting
 fear of regret

Difference in calculating individual vs institutional return requirement
 individual has shorter time horizon (usu) so can use additive
 for institutional or longer term horizons, multiply (1+infl)(1+spend)(1+mgmt fees)

Investors utility from asset mix
 Note: variance, not standard deviation
 equation is for whole percentages
 if use decimals, including std dev in decimal form, change to 0.5
 A = investors risk aversion score from 110, 13 is low risk aversion, 710 is high

shortfall risk
semivariance
target semivariance
 shortfall risk: risk of exceeding a maximum acceptable dollar loss
 semivariance: variance calculated using only returns below the expected return
 target semivariance: semivariance below some target minimum return (as opposed to expected return)

Roy's safety first measure
 Rmar = minimum acceptable return
 IF Rmar < Rf, use Rf

Five criteria for an asset class
 1. Assets are homogenous with high positive correlation
 2. Asset classes are mutually exclusive
 3. Asset classes are diversifying with low correlation
 4. The classes include most of the world's investable assets
 5. Asset classes are sufficiently liquid to allow investment

Determine if an asset class will add value to the portfolio
if AND asset is permissible by the investor's constraints, then asset should be added

Risks of international investments
 Currency
 Home country bias
 Political
 Costs  less liquid; higher transaction costs; free float (market cap greater than investable shares); lack of information; infrastructure and facilities create high clearing and custody fees
 Contagion  correlations are higher in a crisis, when diversification is most needed; could use two correlation matrices, one for normal periods and one for crisis

Integration of markets pros and cons
 Pros: higher capital flow into market could drive up prices; beta becomes the risk rather than standalone risk, which is usually higher; volatility declines; lowers cost of capital, increasing prices and liquidity
 Cons: decreases diversification benefit

Six approaches to asset allocation
 1. meanvariance optimization (MVO)
 2. resampled efficient frontier
 3. blacklitterman
 4. monte carlo simulation
 5. assetliability management
 6. experiencedbased

meanvariance optimization description and cons
 E(r), stnd dev, and correlation are estimated, then put into a model to optimize risk for each return level  aka efficient frontier
 Can be unconstrained (allow short sales) or constrained (only positive weights
 Constrained is more practical as unconstrained can lead to strange/unrealistic weights
 Cons: frontier is unstable  highly sensitive to inputs; maintaining weighting is costly

resampled efficient frontier definition; pros and cons
 like MVO, but inputs have associated probabilities and run through monte carlo
 efficient frontier is more like a blur
 optimal allocation for a single resampled portfolio is the average of possible allocations
 Pros: generates more stable asset allocations; addresses inability to know true input values
 Cons: no statistical rationale for the process; historical initial data may not be indicative of future values

blacklitterman definitions; pros and cons
 manager inputs global asset weights and covariances, and reverse optimizes for implied returns by asset class
 manager can adjust returns based on his outlook on the economy
 final results can be put into an MVO model, or start with the global portfolio and adjust weights based on views
 Pros: by starting with global portfolio, generally produces well diversified portfolios; reduces bias input as returns are anchored to current returns
 Cons: complex and uses historical values that may not reflect future performance

Monte carlo pros and cons
 Pros: overcomes the static nature of MVO; used for ALM analysis
 Cons: complex; expensive; dependent on quality of inputs

ALM definition; pros and cons
 uses MV analysis to optimize growth of surplus in relation to volatility of surplus
 surplus = present value assets (PVA)  PVL
 plot efficient frontier of surplus with far left point being Minimum Surplus Variance (MSV)
 vertical axis of efficient frontier graph is (PVAPVL), horizontal is standard deviation
 Pros: considers allocation of assets with respect to liabilities; can assess probability of meeting liabilities
 Cons: estimation bias; must be incorporated with another approach (ex monte carlo) to address multiperiod concerns

experienced based technique three heuristics; pros and cons
 Use heuristics, such as
 1. Long time horizons increase ability to bear risk
 2. Neutral allocation for the average investor is 60/40
 3. Subtract investors age from 100 to determine preferred allocation to equities
 Pros: generally consistent with more sophisticated techniques; simple and cheap
 Cons: not based on sound investment theory; allocation rules may be too simple for some investors

Corner portfolio theorem (no Rf)
 use small number of corner portfolios to approximate the efficient frontier
 only applies for sign constrained portfolios
 corners are when the weight of an asset go to or from 0 as move from left to right along efficient frontier
 linear combination between corners for desired return, and linear combination to determine final portfolio standard deviation

Addition of Rf to corner portfolio theorem
 Create capital allocation line (CAL) between Rf and portfolio with highest Sharpe ratio
 CAL dominates all other portfolios, other than the tangency portfolio
 Note must be able to short Rf to gain higher return than tangency portfolio

Tactical Asset Allocation
Deviate from the optimal allocation to take advantage of mispricings and add alpha

