No Portfolio is an Island

Transcription

1 Agenda No Portfolio is an Island David Blanchett, CFA, CFP, AIFA Head of Retirement Research Morningstar Investment Management A Total Wealth Approach to Asset Allocation Human Capital Pension Wealth Housing Wealth Total Wealth Extension: Charitable endowments Liability-Relative Investing Efficient Income Investing Optimal Portfolios for the Long Run 2014 Morningstar. All Rights. For Financial Professional Use Only. These materials are for information and/or illustrative purposes only. The Morningstar Investment Management group of Morningstar, Inc. includes Morningstar Associates, Ibbotson Associates, and Morningstar Investment Services, which are registered investment advisors and wholly owned subsidiaries of Morningstar, Inc. All investment advisory services described herein are provided by one or more of the U.S. registered investment advisor subsidiaries. The Morningstar name and logo are registered marks of Morningstar. This presentation includes proprietary materials of Morningstar. Reproduction, transcription or other use, by any means, in whole or in part, without the prior, written consent of Morningstar is prohibited. 1 1 What s Your Investing Goal? One Size Does Not Fit All The Investment Management Process A Total Wealth Perspective 5 5 1

2 No Portfolio is an Island Typical Wealth Perspective 6 6 A Total Wealth Approach A Total Wealth Perspective of Asset Allocation Holistic view of each component of individuals total wealth Objective: Find most efficient combination of available financial assets given a person s human capital and outside wealth = Total Economic Wealth Financial Capital Human Capital Housing Wealth Pension Wealth 9 9 The Total Picture Relative Weights 2

3 How Risky is Human Capital? Asset Class and Human Capital Correlations Asset Class Industry-Specific Human Capital Cons Fin Govt Healt Lodg Manu Mine RE Trans Util Avg Inter LongBnd TIPS HiYld NnUSBd LarGro LarVal SmGro SmVal NnUSEq Commod REITs Building More Efficient Portfolios The optimal portfolio for an investor should deviate from the market portfolio to the extent that he or she is different from everyone else The risks innate to an investor s outside wealth determine hedging needs Ignoring the risks embedded in investor s outside wealth when building a financial asset portfolio assumes that these risks are uncorrelated with financial assets Using Financial Wealth as a Completion Portfolio Financial Wealth Island Portfolio (Tradeable) + Human Capital Wealth + + = Housing Wealth Outside Wealth (Nontradeable) Pension Wealth Optimal Total Wealth Portfolio Incorporating Human Capital Difference to Island Portfolio Incorporating Industry-Specific Human Capital: Difference to Island & Market Portfolio Equity Alt Equity Alt

4 Relation Between Human Beta and Equity Allocations Incorporating Real Estate: Difference to Island Portfolio Equity Alt Incorporating Regional Housing Wealth: Las Vegas Implementing a Total Wealth Approach Target Allocation Adding Guaranteed Income Equity Alt 55% Stock 45% SPIA 25% 30% Stock 45% The remaining non-annuity portfolio now has a 60% equity allocation; however, the total wealth allocation from an income perspective, after considering the Single Premium Immediate Annuity (SPIA), is still 45% equities. For illustration only Charitable Assets An Alternative Way to Consider Total Wealth: Charitable Endowments The wealth of a charity goes beyond it s financial (e.g., endowment) and nonfinancial (e.g., buildings) assets These other assets, that have unique risks (often referred to as background risks) One example of a background risk is donation risk, i.e., the relationship between changes in donor behavior and market returns individuals make ~80% of all charitable donations religious charities are the largest recipient, ~ 33% of total 4

5 % of Total Optimal Portfolios Considering Donation Risk with a 60% Equity Target 100% 90% 80% 70% 60% 50% 40% 30% 20% 10% 0% Donation Type RE Comm EM Intl LarVal LarGro SmVal SmGro Non-US s HY TIPS LongBnd InterBnd Liability-Relative Investing Source: Donation Risk and Optimal Endowment Portfolio Allocations. Morningstar Investment Management White Paper by David Blanchett Optimal Asset Allocation When assets exist to fund a liability, how should the asset allocation policy be determined? The Traditional Approach asset-only mean-variance optimization followed perhaps by a Monte Carlo Simulation Surplus optimization (a.k.a. asset-liability optimization approach) True Risk What is the TRUE risk for a portfolio that exists to fund (pay for) a liability? It is NOT the standard deviation of the asset portfolio It is NOT the performance of your asset portfolio relative to the asset portfolios of your peers The TRUE risk is that it won t be able to pay for the liability! Growth of Liability Driven Investing in the DB Space Improving Portfolio Health % of DB Plans Employing LDI 54% 50% 37% 63% 57% LDI Implementation Methods Assetonly Approach Value of Liabilities vs. Value of Assets Portfolio Health/ Funding Costs Value of Assets Value of Liabilities Portfolio Health 20% Liabilityrelative Approach Source: SEI s 6th Annual Global Liability Driven Investing Poll 5

6 Equity Exposure (%) Expected Return Different Efficient Frontiers Different Portfolios MV Frontier Minimum Surplus Variance Portfolio Liability Surplus Frontier Risk Liability Relative US TIPS Asset-Only US US Non US US TIPS US Large Cap Stock US Small Cap Stock Non US Large Cap Stock Emerging Markets Stock Liability-Relative Asset-Only Return and Risk Impact Scenario One: Return Risk Scenario Two: Surplus Return Risk Source: Alpha, Beta, and Now Gamma Morningstar Investment Management White Paper by David Blanchett and Paul D. Kaplan 100 Generalized Ibbotson Target Maturity Glide Path Within s More Nominal s Long Duration s More Credit Exposure More Non-US s Within s Shift to TIPS Decrease in Duration Decrease in Credit Exposure Decrease in Non-US s Within s More TIPS Shorter Duration Less High Yield Greater US Home s Bias 80 Within Stocks Higher Non-US 60 Higher Emerging Within Stocks Higher Small Cap Average Non-US Average Emerging 40 Average Small Cap Within Stocks Lower 90 Non-US 100 Age 20 Lower Emerging Stocks Lower Small Cap Knowledge Age Bureau, 55 Inc. All Copyright Rights An Income Perspective Efficient Income Investing Limited guidance on how to build an efficient income portfolios Traditional portfolio optimization research focuses on Total Return (which combines Price Return and Income Return), which is an incomplete perspective for a retiree who wants to generate income and not liquidate principal Example: Long-Term bonds held to maturity 6

7 Return Return Price of PFF Average 6 Month Dividend Income Return vs Total Return ishares S&P U.S. Preferred Stock Index Fund (ticker PFF) Source: ishares $60 $0.35 $50 $0.30 $40 $0.25 $30 $0.20 $0.15 $20 $0.10 $10 $0.05 $0 $0.00 Mar-07 Jan-08 Nov-08 Sep-09 Jul-10 May-11 Mar-12 Date Price Average Rolling 6 Month Dividend Income Return, Price Return, and Total Return Income Return Price Return Total Return Asset Class Return Std Dev Return Std Dev Return Std Dev Short-term 3.80% 1.36% 0.00% 2.13% 3.80% 2.73% Intermediate Govt 3.83% 1.41% 0.00% 3.81% 3.83% 4.19% Long Govt 4.05% 0.97% 0.00% 11.24% 4.05% 11.80% Intermediate Credit 4.76% 0.95% 0.00% 5.03% 4.76% 5.43% Long Credit 5.93% 0.77% 0.00% 7.71% 5.93% 8.21% MBS 3.94% 1.47% 0.00% 3.43% 3.94% 3.78% TIPS 3.57% 1.59% 1.18% 5.68% 4.75% 5.25% High Yield 6.84% 0.69% 0.00% 14.73% 6.84% 16.12% International 6.01% 1.62% 0.65% 8.78% 6.66% 9.17% Emerging Markets 7.03% 2.90% 0.76% 13.52% 7.79% 14.65% Large Growth 1.50% 0.44% 8.53% 22.40% 10.03% 22.73% Large Value 2.65% 0.49% 6.92% 17.02% 9.56% 17.53% Small Growth 0.62% 0.13% 11.07% 22.59% 11.69% 22.74% Small Value 2.11% 0.28% 7.94% 17.88% 10.05% 18.22% Preferred Stock 7.50% 0.78% 0.00% 12.74% 7.50% 13.99% Non-US Large Growth 2.59% 0.56% 9.25% 21.83% 11.84% 22.34% Non-US Large Value 4.07% 0.92% 7.87% 21.93% 11.93% 22.57% Emerging Markets Equity 2.60% 0.50% 10.62% 35.65% 13.22% 36.53% Non-US Real Estate 4.20% 0.47% 8.46% 28.60% 12.66% 29.83% US Real Estate 3.00% 1.38% 7.67% 19.57% 10.67% 21.19% Source: Efficient Income Investing Morningstar Investment Management White Paper by David Blanchett and Hal Ratner Efficient Frontier Components Total Return Efficient Frontier vs Income Return Efficient Frontier 14% 12% 10% 8% 6% 4% 2% 0% 0% 10% 20% 30% 40% Standard Deviation Income Return Price Return Total Return 14% 12% 10% 8% 6% 4% 2% 0% 0% 10% 20% 30% 40% Standard Deviation Income Return Efficient Frontier Total Return Efficient Frontier Source: Efficient Income Investing Morningstar Investment Management White Paper by David Blanchett and Hal Ratner Source: Efficient Income Investing Morningstar Investment Management White Paper by David Blanchett and Hal Ratner Differences Impact of Taxes Income-Optimized Portfolio Return-Optimized Portfolio Total Return Income Return Total Return Pre-Tax Post-Tax Pre-Tax Post-Tax 4.50% 7.4% 10.7% 3.2% 4.50% 8.1% 9.2% 1.1% 5.00% 11.7% 16.6% 4.9% 5.00% 11.9% 13.7% 1.9% 5.50% 15.4% 21.9% 6.5% 5.50% 16.1% 19.2% 3.1% 6.00% 18.9% 27.1% 8.2% 6.00% 20.0% 27.1% 7.1% 6.50% 22.5% 32.3% 9.8% 6.50% 23.5% 32.6% 9.1% 7.00% 30.4% 39.6% 9.2% 7.00% 27.1% 38.1% 11.0% Total Return Source: Efficient Income Investing Morningstar Investment Management White Paper by David Blanchett and Hal Ratner Source: Efficient Income Investing Morningstar Investment Management White Paper by David Blanchett and Hal Ratner 7

8 Time Diversification Debate Optimal Portfolios for the Long Run Zvi Bodie, Ph.D. Boston University Having a long time horizon and being risk averse are two completely different things. The popular literature has basically said if you have a long time horizon you're tolerant towards risk. That's the fundamental fallacy. Source: NAPFA 2004 Conference Stocks are relatively safer in the long run than random walk theory would predict. Doesn't mean they're safe. The whole point is that they are relatively safer... Does the fact that equity returns display long run mean reversion change your equity strategy? The answer is definitely yes. Change your allocation strategy? The answer is definitely yes. Source: NAPFA 2004 Conference Jeremy Siegel, Ph.D. Wharton School Holding Period and Standard Deviation Are Returns Random? Source: Campbell, John Y., and Luis M. Viceira. Strategic Asset Allocation: Portfolio Choice for Long-term Investors. Oxford University Press, Accounting for Decreasing Marginal Utility Analysis Rolling return data from 20 countries between 1900 and 2012 (DMS data) Create rolling and distinct periods from 1 to 20 years Estimate growth in portfolios over each rolling period Estimate how much utility we d get from consuming portfolio at end of period Optimize asset allocation that maximizes utility for each set of rolling periods Calculate optimal allocations for varying levels of risk aversion 8

9 Optimal Equity Allocation Level of Risk Aversion Level of Risk Aversion Equity Allocation Optimal Equity Allocation Based on Holding Period Asset Allocation and Holding Period 100% 80% 60% 40% 20% y = x R² = % Investment Period (Years) 100% 80% 60% 40% 20% 0% Year γ = 1 γ = 2 γ = 4 γ = 8 γ = 16 Optimal Equity Allocation Anomalies United States Investment Period (Years) (Very Low) 19 (Very High) 20 Country Average (Very 1 Low) (Very 19 High) Investment Period (Years) Equity Allocation 0%-10% 11%-20% 21%-30% 31%-40% 41%-50% 51%-60% 61%-70% 71%-80% 81%-90% 91%-100% Australia Switzerland How Bad Would it Have to Be? Is Time Diversification Going Away? Average Equity Premium Risk tolerant (y=4), 5 year -0.3% Risk tolerant, 10 year -0.7% Risk tolerant, 20 year -1.6% Risk averse (y=8), 5 year -0.4% Risk averse, 10 year -1.6% Risk averse, 20 year -2.2% Time Diversification Benefit (% increase per year) Optimal Initial Equity Allocation (%) 9

10 Parting Thoughts on Time Diversification Strong evidence that stocks can be more attractive for longrun investors Mean reversion drives long-run equity advantage Reward for ignoring short-run performance Written investment policy statement and target-date funds can help maintain long-run focus Provides empirical evidence for using bucket approaches Conclusions Conclusions Disclosures Financial assets are often only a small part of investor s total wealth (regardless of investor-type) There are different approaches to building portfolios that result in different right answers The risk of equities is not static over time 2014 Morningstar. All rights reserved. For information and/or illustrative purposes only. Not for public distribution. The Morningstar Investment Management group of Morningstar, Inc. includes Morningstar Associates, Ibbotson Associates, and Morningstar Investment Services, which are registered investment advisors and wholly owned subsidiaries of Morningstar, Inc. The information contained in this presentation is the proprietary material of Ibbotson Associates. Reproduction, transcription or other use by any means, in whole or in part, without the prior written consent of Ibbotson Associates, is prohibited. The Morningstar name and logo are registered marks of Morningstar, Inc. The Ibbotson name and logo are registered marks of Ibbotson Associates, Inc. The above commentary is for informational purposes only and should not be viewed as an offer to buy or sell a particular security. The data and/or information noted are from what we believe to be reliable sources, however we have no control over the means or methods used to collect the data/information and therefore cannot guarantee their accuracy or completeness. The opinions and estimates noted herein are accurate as of a certain date and are subject to change. The indexes referenced are unmanaged and cannot be invested in directly. Past performance is not a guarantee of future results. The charts and graphs within are for illustrative purposes only. Monte Carlo is an analytical method used to simulate random returns of uncertain variables to obtain a range of possible outcomes. Such probabilistic simulation does not analyze specific security holdings, but instead analyzes the identified asset classes. The simulation generated is not a guarantee or projection of future results, but rather, a tool to identify a range of potential outcomes that could potentially be realized. The Monte Carlo simulation is hypothetical in nature and for illustrative purposes only. Results noted may vary with each use and over time. The results from the simulations described within are hypothetical in nature and not actual investment results or guarantees of future results. This should not be considered tax or financial planning advice. Please consult a tax and/or financial professional for advice specific to your individual circumstances