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

Level III Principles of Asset Allocation Summary Graphs, charts, tables, examples, and figures are copyright 2017, CFA Institute Reproduced and republished with permission from CFA Institute All rights reserved 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 www.ift.world Criticisms of Mean–Variance Optimization The outputs (asset allocations) are highly sensitive to small changes in the inputs The asset allocations tend to be highly concentrated in a subset of the available asset classes Many investors are concerned about more than the mean and variance of returns, the focus of MVO Although the asset allocations may appear diversified across assets, the sources of risk may not be diversified 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 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 www.ift.world Recommend and Justify Asset Allocation Based on MVO Portfolio Number Expected Nominal Returns 9.50% 8.90 8.61 7.24 5.61 5.49 3.61 Standard Deviation 18.00% 15.98 15.20 11.65 7.89 7.65 5.39 Sharpe Ratio 0.406 0.419 0.422 0.433 0.432 0.430 0.262 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 www.ift.world 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 www.ift.world 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 www.ift.world Risk Budgeting The goal of risk budgeting is to maximize return per unit of risk Three aspects of risk budgeting: The risk budget identifies the total amount of risk and allocates the risk to a portfolio’s constituent parts An optimal risk budget allocates risk efficiently 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 www.ift.world 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 www.ift.world 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 Exhibit 20 Factors/Asset Classes, Factor Definitions, and Historical Statistics (US data, January 1979 to March 2016) Factor/Asset Class Cash Market Size Valuation Credit Duration Factor Definition 3-Month Treasury bills Total market return – Cash Small cap – Large cap Value – Growth Corporate – Treasury Long Treasury bonds – Treasury bills Compound Annual Factor Return Standard Deviation 7.49% 0.41 0.68 0.70 4.56 16.56% 10.15 9.20 3.51 11.29 Total Return 7.77% 12.97 5.56 5.84 5.87 9.91 Standard Deviation 5.66% 17.33 10.65 9.76 3.84 11.93 Asset allocation should be performed in a space (risk factors or asset classes) where one is best positioned to make capital market assumptions Expanding opportunity set to include new, weakly correlated risk factors or asset classes will improve risk–return trade-off www.ift.world 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 www.ift.world 10 Characteristics of Liabilities That Can Affect Asset Allocation Fixed versus contingent cash flows Legal versus quasi-liabilities Duration and convexity of liability cash flows Value of liabilities as compared with the size of the sponsoring organization Factors driving future liability cash flows Timing considerations, such as longevity risk Regulations affecting liability cash flow calculations www.ift.world 11 Approaches to Liability-Relative Asset Allocation Surplus optimization Select asset categories and determine planning horizon Estimate returns and volatilities for assets and liabilities Determine constraints Estimate correlations Compute surplus efficient frontier Select recommended portfolio 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 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 Integrated asset-liability approach is appropriate when decisions regarding composition of liabilities are made in conjunction with asset allocation Useful for banks, long-short hedge funds, insurance and re-insurance companies www.ift.world 12 Surplus Optimization Simplicity Linear correlation All levels of risk Any funded ratio Single period Hedging/Return-Seeking Portfolios Simplicity Linear or non-linear correlation Conservative level of risk Positive funded ratio for basic approach Single period Integrated Asset–Liability Portfolios Increased complexity Linear or non-linear correlation All levels of risk Any funded ratio Multiple periods Recommend and Justify a Liability-Relative Asset Allocation www.ift.world 13 Goals-Based Asset Allocation Process Exhibit 34: Goals-Based Asset Allocation Process Goals can be categorized as: • needs • wants • wishes • dreams Goals can then be assigned an appropriate probability of success www.ift.world 14 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 Expected volatility Time Horizon (years) 99% 95 90 75 Time Horizon (years) 95% 90 85 75 A 4.3% 2.7% B 5.5% 4.5% C 6.4% 6.0% D 7.2% 7.5% E 8.0% 10.0% F 8.7% 12.5% –0.6% 1.7 2.9 4.9 –2.4% 0.7 2.3 5.0 –4.3% –0.5 1.5 4.9 4.4% 5.0 5.4 6.0 4.4% 5.2 5.7 6.5 4.1% 5.1 5.8 6.8 1.5% 2.3 2.7 3.5 0.9% 2.2 3.0 4.2 0.2% 2.0 3.0 4.6 20 3.3% 3.5 3.7 3.9 3.9% 4.3 4.5 4.9 4.2% 4.7 5.0 5.5 500,000 488,759 510,000 487,325 520,200 485,896 530,604 484,471 541,216 483,050 2,429,502 Overall allocation is the weighted average exposure to each of the asset classes within each module www.ift.world 15 Heuristics and Other Approaches to Asset Allocation Heuristic: rule that provides a reasonable but not necessarily optimal solution Heuristic Comment Critique “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 www.ift.world 16 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 Risk tolerance Correlation with the rest of the portfolio Volatility of an illiquid asset class Volatility of the rest of the portfolio The higher the transaction costs, the wider the optimal corridor The higher the risk tolerance, the wider the optimal corridor The higher the correlation, the wider the optimal corridor The higher the volatility, the higher the optimal corridor The higher the volatility, the narrower the optimal corridor www.ift.world High transaction costs set a high hurdle for rebalancing benefits to overcome Higher risk tolerance means less sensitivity to divergences from the target allocation When asset classes move in sync, further divergence from target weights is less likely Containing transaction costs is more important than expected utility losses Higher volatility makes large divergences from the strategic asset allocation more likely 17 ... 0.9% 2.2 3. 0 4.2 0.2% 2.0 3. 0 4.6 20 3. 3% 3. 5 3. 7 3. 9 3. 9% 4 .3 4.5 4.9 4.2% 4.7 5.0 5.5 500,000 488,759 510,000 487 ,32 5 520,200 485,896 530 ,604 484,471 541,216 4 83, 050 2,429,502 Overall allocation. .. 10.15 9.20 3. 51 11.29 Total Return 7.77% 12.97 5.56 5.84 5.87 9.91 Standard Deviation 5.66% 17 .33 10.65 9.76 3. 84 11. 93 Asset allocation should be performed in a space (risk factors or asset classes)... making asset allocation decisions www.ift.world Criticisms of Mean–Variance Optimization The outputs (asset allocations) are highly sensitive to small changes in the inputs The asset allocations