CFA 2018 level 3 schweser practice exam CFA 2018 level 3 question bank CFA 2018 r17 principles of asset allocation summary

Recommend and Justify Asset Allocation Based on MVOPortfolio Number Expected Nominal Returns Standard Deviation Sharpe Ratio The portfolios shown are corner portfolios which as a group

Level III

Principles of Asset Allocation

Summary

Mean–Variance Optimization

Mean-variance optimization (MVO) provides a framework for determining how much to allocate to

each asset in order to maximize portfolio’s expected return at a given level of risk MVO is a risk

budgeting tool which helps investors spend their risk budget wisely.

Client needs and preferences must be considered in making asset allocation

decisions

Criticisms of Mean–Variance Optimization

1 The outputs (asset allocations) are highly sensitive to small changes in the inputs

2 The asset allocations tend to be highly concentrated in a subset of the available asset classes

3 Many investors are concerned about more than the mean and variance of returns, the focus of MVO

4 Although the asset allocations may appear diversified across assets, the sources of risk may not be diversified

5 Most portfolios exist to pay for a liability or consumption series, and MVO allocations are not directly

connected to what influences the value of the liability or the consumption series

6 MVO is a single-period framework that does not take account of trading/rebalancing costs and taxes

Some techniques for addressing the limitations of MVO:

• Reverse optimization

• Reverse optimization tilted toward an investor’s views on asset returns (Black–Litterman)

• Constraints on asset class weights to prevent extremely concentrated portfolios

• Resampled efficient frontier

Recommend and Justify Asset Allocation Based on MVO

Portfolio

Number Expected Nominal Returns

Standard Deviation

Sharpe Ratio

The portfolios shown are corner portfolios which as a group define the risky-asset efficient frontier in the sense that any portfolio on the frontier is a combination of the two corner portfolios that bracket it in terms of expected return

A foundation’s return objective is 6.5% The risk free rate is 2.2%

Determine the most appropriate strategic asset

Asset Allocation and Economic Balance Sheet

Emma Beel is a 45-year-old tenured

university professor in London

• GBP 1,500,000 in liquid financial assets

• NPV of human capital ≈ GBP 500,000

• Inherited home valued at GBP 750,000

Liquidity Considerations

Less liquid asset classes include direct real estate, infrastructure and private equity; offer illiquidity

return premium

Two major problems associated with less liquid asset classes:

• Lack of accurate indexes  challenging to make capital market assumptions

• Difficult to diversity and no low-cost passive investment vehicles

Practical options of investing in less liquid assets:

• Exclude less liquid asset classes; then consider real estate funds, infrastructure funds, and private equity funds.

• Include less liquid asset classes in the asset allocation decision and model the specific risk

characteristics associated with the implementation vehicles.

• Include less liquid asset classes in the asset allocation decision and model the inputs to represent the highly diversified characteristics associated with the true asset classes.

Risk Budgeting

The goal of risk budgeting is to maximize return per unit of risk

Three aspects of risk budgeting:

1 The risk budget identifies the total amount of risk and allocates the risk to a portfolio’s

constituent parts.

2 An optimal risk budget allocates risk efficiently.

3 The process of finding the optimal risk budget is risk budgeting.

Marginal contribution to total risk (MCTR) = rate at which risk changes with a small change in the

current weights = (Beta of asset class i with respect to portfolio) x (Portfolio return volatility)

Absolute contribution to total risk (ACTR) = amount asset class contributes to portfolio return volatility

= (Weighti)(MCTRi)

Asset allocation is optimal from a risk-budgeting perspective when the ratio of excess return (over the risk-free rate) to MCTR is the same for all assets and matches the Sharpe ratio of the tangency portfolio.

Monte Carlo Simulation

• Monte Carlo simulation complements MVO

▪ Handles multiple periods

▪ Realistic picture of potential future outcomes

▪ Impact of trading, rebalancing and tax costs

• Monte Carlo simulation is particularly important when there cash inflows/outflows and returns vary over time

• Monte Carlo simulation allows us to evaluate robustness of an asset allocation

Factor-Based Asset Allocation

Investment opportunity set can consist of investment factors

• Factors are based on observed market premiums and anomalies

• Factors used in asset allocation include: market exposure, size, valuation, momentum, liquidity,

duration (term), credit, and volatility

Factor/Asset Class Factor Definition

Compound Annual Factor Return

Standard Deviation

Total Return

Standard Deviation

Asset allocation should be performed in a space (risk factors or asset classes) where one is best

positioned to make capital market assumptions

Exhibit 20 Factors/Asset Classes, Factor Definitions, and Historical Statistics (US data, January 1979 to March 2016)

Recommend and Justify Asset Allocation Based on Global

Market Portfolio

Global market-value weighted portfolio should be the baseline asset allocation

• Represents all investable assets  minimizes non-diversifiable risk

• Investing in the global market portfolio helps mitigate investment biases such as home country bias

Proxies for the global market portfolio are often based only on traded assets, such as portfolios of exchange-traded funds (ETFs)

Global market portfolio is used a starting point in the reverse optimization process

Characteristics of Liabilities That Can Affect Asset Allocation

1 Fixed versus contingent cash flows

2 Legal versus quasi-liabilities

3 Duration and convexity of liability cash flows

4 Value of liabilities as compared with the size of the sponsoring organization

5 Factors driving future liability cash flows

6 Timing considerations, such as longevity risk

7 Regulations affecting liability cash flow calculations

Approaches to Liability-Relative Asset Allocation

Surplus optimization

1 Select asset categories and determine planning horizon

2 Estimate returns and volatilities for assets and liabilities

3 Determine constraints

4 Estimate correlations

5 Compute surplus efficient frontier

6 Select recommended portfolio

Hedging/return-seeking portfolios approach

Part 1: Asset allocation for liability hedging portfolio

▪ Possible techniques: cash flow matching, duration matching, immunization

▪ Factors driving asset returns ≈ factors driving liability returns

Part 2: Asset allocation for return-seeking portfolio

▪ Mean-variance optimization

Integrated asset–liability approach

Expected surplus return = (Δ asset value – Δ liability value) / Initial asset value

Δ liability value (or liability return) measures time value of money for liabilities plus any expected changes in the discount rate and future cash flows over the planning horizon

Integrated asset-liability approach is appropriate when decisions regarding

Recommend and Justify a Liability-Relative Asset Allocation

Surplus Optimization Hedging/Return-Seeking Portfolios Integrated Asset–Liability Portfolios

Linear correlation Linear or non-linear correlation Linear or non-linear correlation

All levels of risk Conservative level of risk All levels of risk

Any funded ratio Positive funded ratio for basic approach Any funded ratio

Goals-Based Asset Allocation Process

Exhibit 34: Goals-Based Asset Allocation Process

Goals can be categorized as:

• wishes

Goals can then be assigned an

The Smiths have financial assets worth US$25 million The parents are in their mid-fifties, and the household spends about US$500,000 a year They expect that inflation will average about 2% per year for the foreseeable future They express four important goals and are concerned that they may not be able to meet all of them:

• They need a 95% chance of being able to maintain their current expenditures over the next five years

• They wish to have a 75% chance to be able to create a family foundation, which they wish to fund with US$10 million in 20 years.

Expected return 4.3% 5.5% 6.4% 7.2% 8.0% 8.7%

Expected volatility 2.7% 4.5% 6.0% 7.5% 10.0% 12.5%

Time Horizon (years) 20

500,000 488,759 510,000 487,325 520,200 485,896 530,604 484,471 541,216 483,050

2,429,502

Overall allocation is the weighted average exposure to each of the asset classes within each module.

Heuristics and Other Approaches to Asset Allocation

Heuristic: rule that provides a reasonable but not necessarily optimal solution

“120 minus your age”

rule

120 – Age = Percentage allocated to stocks

Lacks nuances of target date funds’ glide paths

60/40 stock/bond

heuristic

Provides growth through stocks and risk reduction through bonds

Does not consider investor circumstances

Endowment model Large allocations to non-traditional

investments driven by investment manager skill

Complex and high-cost

Risk parity Each asset class should contribute

equally to total risk

Ignores expected returns; contribution to risk is highly dependent on the formation of the

investment opportunity set 1/N rule Equal weight to all asset classes Asset classes treated as indistinguishable in

terms of returns, volatility and correlations

Factors Affecting Rebalancing Policy

SAA is the optimal allocation for an investor  sticking to SAA represents a benefit; deviating from SAA represents a loss in utility

Disciplined rebalancing reduces risk and adds to return

Two major strategies: calendar rebalancing and percent-range rebalancing

• Calendar rebalancing has a lower cost

• Percent-range is a more disciplined risk control policy

▪ Rebalance to actual SAA weights or upper/lower edge or somewhere in between?

▪ What is the optimal corridor width?

Transaction costs The higher the transaction costs, the

wider the optimal corridor.

High transaction costs set a high hurdle for rebalancing benefits to overcome.

Risk tolerance The higher the risk tolerance, the wider

the optimal corridor.

Higher risk tolerance means less sensitivity to divergences from the target allocation.

Correlation with the rest of the

portfolio

The higher the correlation, the wider the optimal corridor.

When asset classes move in sync, further divergence from target weights is less likely.

Volatility of an illiquid asset class The higher the volatility, the higher the

optimal corridor.

Containing transaction costs is more important than expected utility losses.