Asset Allocation Flashcards
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Asset Allocation Approaches: Investment Objective
1. Asset Only:
- Use MVO,
- max port’s sharpe,
- diversification, correlations with other assets you hold and liquidity are also relevant
2. Liability Relative:
- duration, inflation and credit-risk should be closely monitored.
- Fund status impacts the risk profile b/w liability-hedging and return seeking (why increase risk if you are overfunded?).
3. Goal-based asset allocation:
- built into behavioral finance (mental accounting bias).
- Adds riskier assets that are accepted by the investor due to its context in the portfolio
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Super asset classes
as defined by Greer (1997)
1. Capital Assets - generates dividends, CF or interest - value determined by NPV (eg. stocks, bonds, etc)
2. Consumable/transformable assets - commodities that are transformed into something else (eg. petroleum)
3. Store of value assets - no income or economic value (eg. art, currencies, precious metals except in industrial application)
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Criteria for specifying an Asset Class
Greer (1997)
1. Homogeneous - similar attributes
2. Mutually Exclusive - Overlapping is a problem (eg. Emerging mkt are a diff class)
3. Diversifying - ρ w/ other class > 0.95 = undesirable.
4. Must be representable
5. Capacity for allocation / Liquidity
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Expected Utility (MVO)
Um = E(Rm) − 0.005 * λ * σ2m
Certainty-equivalent return (comparable to the risk-free**)
where
λ = the investor’s risk aversion coefficient - investor’s risk-return trade-off (how much inv will forgo return for lowering risk). 0 = risk neutral 4 = risk moderate
DEIXAR O RESTANTE EM % MESMO > 14%² = 196
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SFRatio vs Sortino Ratio
RSF = (RP – MinimumAcceptableReturn) / σP
Sortino = (RP – MinimumAcceptableReturn) / Downside Deviation
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SFRatio
RSF = (RP – MinimumAcceptableReturn) / σP
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Criticisms of MVO
- Highly concentrated / Too sensitive (large shifts w/ small changes)
- Assumes a normal distribution of returns.
- Diversification by asset class ≠ diversification by risk source
- Single-period model = ignores taxes, transaction costs, inflation or liabilities.
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Criticisms of MVO
X Highly concentrated / Too sensitive (large shifts w/ small changes)
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Reverse optimization - less dependent on estimates of return.
- Start with ρ, σ, and benchmark weights (or another optimal target).
- Then use MVO to solve for expected return by asset class.
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Black-Litterman - less dependent on estimates of return and tends to include more classes
- Reverse optimization + Manager views to adjust MVO
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Monte Carlo (Resampling) - deals directly with the uncertainty of estimating returns.
- It starts with MVO and the manager’s best estimates of return and other inputs.
- Then the return data is varied up and down (Monte Carlo). The avg EF of each allocation is selected.
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Criticisms of MVO
Diversification by asset class ≠ diversification by risk source
- Factor-based allocation (i.e. mkt risk premium, mkt cap, value vs. growth, mkt momentum vs. mean reversion, duration, etc)
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Criticisms of MVO
Assumes a normal distribution of returns.
Non-normal optimization
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Criticisms of MVO
Single-period model
- Goals based approach – suited to individuals w/ multiple goals (sub-portfolios)
- Liability-relative Asset Allocation – model liabilities as part of MVO and use Monte Carlo on how portfolio performs over time
- Surplus optimization: surplus efficient frontier (min Vol & max Er)
- “two-portfolio”: Hedging / Return seeking portfolio (for the surplus)
- Asset-liability approach (ALM): simultaneously alter charact. of assets and liabilities. Multi-period, more complex.
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- *Risk Budgeting**
- “use risk efficiently in the* persuit of return”
Marginal Contribution to Risk (MCTR)
Absolute Contribution Total Risk (ACTR)
% Contribution to Total Risk
Ratio of Excess Return to MCTR
- *MCTR =** βAsset x σPortfolio
- Excess Return to MCTR = (Er - Rf) / MCTR*
- *ACTR =** WeightAsset x MCTR
- total sum is equal to the portfolio’s risk*
% Contribution to Total Risk = ACTR / Portfolio σ
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Optimal corridor size
(+) related to the optimal corridor size:
Risk Tolerance
Correlation of asset classes
Transaction Costs
(-) related to the optimal corridor size:
Volatile asset class
Volatile portfolio
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Heuristic asset allocation
5 strategies that simplify allocation
- 120 - age (exposure to equity)
- 60/40 stock/bond
- Endowment Model - large allocation to non-traditonal assets
- Risk Parity - distributes equally the risk b/w assets in a port
- The 1/N rule - equally weighted asset allocation (regret aversion)
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Behavioral Biases in Asset Allocation
FILMAR
- Framing
- Illusion of Control
- Loss Aversion
- Mental Accounting
- Availability
- Representativeness
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FX - Return & volatility
RDC = (1 + RFC) * (1 + RFX) -1
<span>σ2</span>(RDC) ≈ <span>σ2</span>(RFC) + <span>σ2</span>(RFX) + 2 * <span>σ</span>(RFC) * <span>σ</span>(RFX) * ρ(RFC,RFX)
REMEMBER: <span>σ2 = Variance; σ = STD Dev = Volatility</span>
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Hedge ratio
Hedge ratio = ρ * σDC / σFX
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Using Sharpe to check if an Asset improves mean-variance
SharpeAsset > SharpePortfolio * ρ
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Hedging Multiple FX
Mostly used when one asset (FX) is held long and the other short. If you have 2 FX with high correl, but both long, you will have to hedge both positions
- Cross hedges – one currency is used to hedge another that is similar, but not exact (correlations may change and expose port)
- Macro hedges – hedge portfolio-wide risk instead of single currency risk. Short a basket of currencies (derivative). Less expensive
- A minimum variance hedge ratio (MVHR) - regression-based approach = cross hedge + macro hedge. H = [σ(InvestorFX) / σ(ExposureFX)] * ρ
- Texas Hedge – Opposite of hedge, doubles the exposure
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FX Hedge Strategies
- Passive: Match FX exposure of benchmark
- Discretionary: risk reduction with deviations from the benchmark to add value.
- Active: Allow wider deviations.
- Overlay: separate manager for FX management. Treat currency as an asset class (pure value-added approach).
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Shrinkage estimator
Shrinkage estimation = weighted avg of a parameter + weighted parameter reflecting analyst’s relative belief
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Hedging emerging market currencies challenges
challenges:
(1) larger bid-asked spreads that expand during crises,
(2) returns negative skew and fat tails,
(3) correlations rise during crisis,
(4) tail risk as governments support FX with severe currency value correction after,
(5) restrict flow - solution = NDF (net settlement in the developed country FX)