Exotic Beta Revisited November 2014 This presentation is for informational purposes only and addresses certain points made in the academic paper referenced herein, the full text of which is available in Carhart, M., Cheah, U., De Santis, G., Farrell, H. and Litterman, B., (2014). Exotic Beta Revisited. Financial Analysts Journal, Volume 70 (Issue 5). doi: /faj.v70.n5.4. The opinions, data and analyses contained herein are solely with respect to such academic paper. Such opinions, data and analyses are as of the date written, and are subject to change without notice. Nothing contained herein should be considered investment advice or an offer or solicitation to buy or sell any investment.doi

Outline 1.A Taxonomy of Exotic Betas 2.Empirical Evidence on Exotic Betas 3.Comparing Alternative Risk Premium Approaches 4.A Dynamic Portfolio of Exotic Betas 5.Closing Remarks

Challenge: Allocation decisions reflect unintended factor exposures Challenge of Policy Allocation Proposed Solution: Purposeful and explicit allocation to risk premia Better knowledge of return sources Conventional Approach Capital-Based Allocations Risk Factor Approach Multiple Risk Premia within Asset Classes Asset Classes Risk Premia Themes

The Return Spectrum Alpha Macro statistical arbitrage Volatility arbitrage Systematic events Exotic Beta Long term value Income Long term momentum Insurance Beta Global equities Active Higher cost Passive Lower cost “…returns exist along a continuum – from beta, to exotic beta, and ultimately to alpha.” – Litterman (2005) ProprietaryWell-known

We focus on four risk premia themes across all four major asset classes. A Taxonomy of Risk Premia Value Equities RISK PREMIUM THEMES ASSET CLASSES BondsCurrenciesCommodities Income Insurance Momentum Cheap assets tend to outperform expensive assets Investors demand additional yield for lower volatility assets Risk averse investors pay a premium to insure against extreme events Asset performance can be persistent

Building an Exotic Beta Portfolio Choose a carry measure Construct a dollar-neutral FX portfolio on carry rank Hedge away ACWI beta using liquid equity index futures FX Carry PortfolioMSCI ACWI Hedge 3-Month LIBOR FX Carry Portfolio 123

Comparing Theoretical and Tradable Exotic Betas Tradable Exotic Beta Portfolios are obtained as follows: Use only tradable assets (e.g. liquid futures contracts) Penalize tracking error from theoretical Exotic Beta portfolio Charge for transaction costs

Distribution of Equity Beta Estimates for Exotic Beta Portfolios

Historical Evidence: ACWI and Individual Exotic Betas All portfolios are normalized to 10% target vola tility Key Takeaways 1.Attractive potential returns 2.Low cross-correlation 3.Poor performance does not correspond with poor performance in equities

Sampling period: January 1990 – December 2012 Summary Statistics for Exotic Beta Portfolios

Return Correlations for Exotic Beta Portfolios Average correlation is 0.04 Using three-year window estimates: -Average correlation is between and Less than 7% of all the correlations are larger than 0.35 (in absolute value)

Cumulative Excess Retruns: ACWI and Equal Risk Exotic Beta Portfolio 1994 run-up in sovereign bond yields LTCM blow up and tech bubble

Risk Parity Main idea: Scale investment in different asset classes to the same risk Combine scaled asset class investments into an equally weighted portfolio

Risk Parity (Across Asset Classes): Return Correlations Average correlation is 0.23 Using three-year window estimates: -Average correlation is between 0.12 and More than 25% of all the correlations are larger than 0.5 (in absolute value)

Understanding Implied Views The common idea that the risk parity portfolio has no views on expected returns is a misconception

Comparing Alternative Investment Strategies Risk parity and hedge funds explain very little of the return variation in the exotic beta portfolio Conditional alpha is almost identical to unconditional alpha for the exotic beta portfolio The exotic beta portfolio offers Better return/risk profile Less extreme DD/vol More attractive diversification Can we explain exotic beta returns?

Estimated Premiums and Correlations Some correlations are high, due to a common ACWI exposure  Most realized returns are biased, due to overfitting, unusual circumstances, survivorship and backfilling bias, etc.  We use the Black-Litterman model to shrink historical returns towards a CAPM equilibrium

Efficient Frontier and Risk-Return Trade-Offs 60% Global Equities 30% Global Bonds 10% Hedge Funds 37% Global Bonds 37% Hedge Funds 26% Exotic Beta 28% Global Bonds 39% Hedge Funds 33% Exotic Beta 60% Global Equities 40% Global Bonds

Risk Budgeting: Out of Sample Evidence 41% Hedge Funds 38% Exotic Beta 21% Global Bonds 2005 Max SR Portfolio 42% Hedge Funds 35% Exotic Beta 23% Global Bonds 2008 Max SR Portfolio

Outline 1.A Taxonomy of Exotic Betas 2.Empirical Evidence on Exotic Betas 3.Comparing Alternative Risk Premium Approaches 4.A Dynamic Portfolio of Exotic Betas 5.Closing Remarks

Equal-Risk Exotic Beta Portfolio Uses only backward-looking estimates of volatilities and correlations Targets 10% volatility Rebalances on a monthly frequency Incorporates t-cost penalties Exotic Beta Portfolio: Equal-Risk vs. Dynamic-Risk Allocations Dynamic-Risk Exotic Beta Portfolio Same as Equal-Risk Exotic Beta Portfolio Incorporates conditional views on the risk premiums based on: −Prior −Historical means −Value −Momentum −Spillover (Market Disruption) Imposes penalties on position and trade size

Conditional Forecasts of an Exotic Beta: Currency Carry

Exotic Beta Portfolio: Equal vs. Dynamic Risk Allocation  Marginal contribution to risk from timing model is 27%  Average turnover of the Dynamic portfolio is 9 months

Outline 1.A Taxonomy of Exotic Betas 2.Empirical Evidence on Exotic Betas 3.Comparing Alternative Risk Premium Approaches 4.A Dynamic Portfolio of Exotic Betas 5.Closing Remarks