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1 Hedge Funds: A Dynamic Industry in Transition Andrew W. Lo, MIT and AlphaSimplex th Anniversary esayco Conference ee March 10, 2016 Based on Getmansky, Lee, and Lo, Hedge Funds: A Dynamic Industry in Transition, Annual Review of Financial Economics (2015) 7: , and Lo, What Is An Index? Journal of Portfolio Management (2016) 42:2, by Andrew W. Lo

2 Congratulations! Slide 2

3 My First Talk: November 19, 1993 Slide 3

4 Have Alternatives Become Irrelevant? Dec 22, 2012 Mar 21, 2013 Jan Jan 1, 1, 2016 Slide 4

5 Have Alternatives Become Irrelevant? Jul 25, 2002 Mar 27, 2005 Nov 22, 2005 Slide 5

6 News of my death is greatly exaggerated January 20, 2016 Slide 6

7 News of my death is greatly exaggerated Hedge Fund Assets Under Management 10 Mar by Andrew W. Lo Source: BarclayHedge Page 7

8 Investors Love/Hate Relationship With Hedge Funds $20 $18 U.S. Treasury Bills Stock Market Pfizer Fairfield Sentry Return$14 Cumulativ ve $16 $14 $12 $10 $8 $6 $4 $2 $ Slide 8

9 Investors Love/Hate Relationship With Hedge Funds Investors Love: Diversification benefits Performance potential Lack of constraints Sophistication Mystique Investors Hate: Lack of transparency Lack of liquidity Limited capacity High fees Operational risks Manager risk Black swan risk Beta disguised as alpha Slide 9

10 Pre- and Post-Crisis Hedge Fund Performance Category # Fund- Months Ann. Mean (%) Ann. SD (%) Sharpe Ratio Sortino Ratio Skew. Kurt. MaxDD (%) Corr. to S&P 0 (%) ρ 1 (%) Box-Q(3) p-value (%) January 1996 to December 2006 Convertible Arbitrage 7, Dedicated Short Bias 1, Emerging Markets 12, Equity Market Neutral 11, Event Driven 18, Fixed Income Arbitrage 7, Global Macro 8, Long/Short Equity Hedge 69, Managed Futures 13, Multi-Strategy 8, Fund of Funds 55, All Single Manager Funds 163, January 2010 to December 2014 Convertible Arbitrage 3, Dedicated Short Bias Emerging Markets 22, Equity Market Neutral 8, Event Driven 11, Fixed Income Arbitrage 7, Global Macro 16, Long/Short Equity Hedge 66, Managed Futures 23, Multi-Strategy 57, Fund of Funds 139, All Single Manager Funds 233, Source: Getmansky, Lee, Lo (2015, Table 14) Slide 10

11 Measuring and Managing Liquidity Autocorrelation can capture illiquidity (Getmansky, Lo, Makarov, 2004) Illiquidity premium is important source of hedge-fund returns But there s tail risk implicit in illiquid assets (flight to safety) Slide 11

12 A New Investment Paradigm Is Emerging In the beginning Implications: Correlation matters; diversification Benchmarks, performance attribution Passive investing Indexation and hedging g Portable alpha overlays Risk budgeting Framework for fiduciary duties Slide 12

13 A New Investment Paradigm Is Emerging But This Framework Requires Several Key Assumptions: Relationship is linear Relationship is static across time and circumstances Parameters can be accurately estimated Investors behave rationally Markets are stationary (static probability laws) Markets are efficient i What If Some of These Assumptions Don t Hold? Slide 13

14 A New Investment Paradigm Is Emerging Cumulative Return of S&P 0 (log scale) January 1926 to December 2015 But Do They Still Hold Today?? Source: CRSP and author s calculations. Slide 14

15 A New Investment Paradigm Is Emerging The Adaptive Markets Hypothesis: 1. Individuals act in their own self-interest 2. Individuals make mistakes ( satisfice ) The Adaptive 3. Individuals learn and adapt (heuristics) Markets 4. Competition drives adaptation and innovation 5. Eoltiondeterminesmarketdnamics Evolution market dynamics Hypothesis Nothing Makes Sense in Biology Except in the Light of Evolution, Dobzhansky (1973) Nothing Makes Sense in the Hedge Fund Industry Except in the Light of the Adaptive Markets Hypothesis, Lo (2016) Slide 15

16 A New Investment Paradigm Is Emerging Efficient Markets Long-only only constraint Diversify across stocks and bonds Market-cap-weighted indexes Manage risk via asset allocation Alpha vs. market beta Markets are efficient Equities in the long run Adaptive Markets Long/short strategies Diversify across more asset classes and strategies Passive transparent indexes Manage risk via active volatility scaling algorithms Alphas multiple betas Markets are adaptive In the long run we re all dead, but make sure the short run doesn t kill you first Slide 16

17 Hedge Funds: The Galapagos Islands of Finance 2% 200% 1% 100% % 0% -% Managed Futures Global Macro -100% Convert Arb Short Bias ED Distressed Emerging Mkts -1% Fixed Income Arb L/S Equity Multi-Strategy Mkt Neutral -200% ED Risk Arb S&P 0 Barclay Bond -2% Slide 17

18 Hedge Funds: The Galapagos Islands of Finance Example: Paulson & Co. (Wall Street Journal, January 5, 2009) Slide 18

Hedge Funds: The Galapagos Islands of Finance Other

momentum, earnings surprise ABS, MBS, CDO, structured

arbitrage Merger arbitrage Trend-following The carry

19 Hedge Funds: The Galapagos Islands of Finance Other Examples of Alpha Turning To Beta Value, growth, momentum, earnings surprise ABS, MBS, CDO, structured credit Equity market neutral Fixed-income income arbitrage Merger arbitrage Trend-following The carry trade etc. Wall Street Journal September 7, Mar by Andrew W. Lo Slide 19

20 Hedge Funds: The Galapagos Islands of Finance Equity Market Neutral Fund Dynamics Source: Getmansky, Lee, Lo (2016, Fig. 9) Slide 20

21 Hedge Funds: The Galapagos Islands of Finance Fixed Income Arbitrage Fund Dynamics Source: Getmansky, Lee, Lo (2016, Fig. 9) Slide 21

22 Hedge Funds: The Galapagos Islands of Finance α α α α α α α α α α α α α α α α α α α α α α α α Unique Novel Popular Common Slide 22

23 Hedge Funds: The Galapagos Islands of Finance Slide 23

24 Hedge-Fund Betas Betas Hedge Fund Category Annualized Categor ry Volatility R Squared Mon nthly Alpha Equ uity Market Factor Lag gged Equity Ma arket Factor Size Sp read Factor Bo ond Market Factor Annualized Factor Volatility: 15.4% 11.4% 11.8% 3.5% Convertible Arbitrage 7.3% % Dedicated Short Bias 15.6% % Emerging Markets 14.2% % Equity Market Neutral 3.3% % Event Driven 5.9% % Fixed Income Arbitrage 4.4% % Global l Macro 52% 5.2% % 0.10% Long/Short Equity Hedge 9.0% % Managed Futures 9.4% % Multi-Strategy 5.2% % Fund of Funds 6.0% % All Single Manager Funds 6.3% % Correlation with Equity Factor: Slide 24

25 Hedge-Fund Betas Out-of-Sample R 2 Comparison of Factor Models* January 1998 to December 2014 Hedge Fund Category Fung & Hsieh 7- Factor Model Investable 4- Factor Model Convertible Arbitrage 49% 31% Dedicated Short Bias 57% 66% Emerging Markets 36% 45% Equity Market Neutral -6% 14% Event Driven 52% 56% Fixed Income Arbitrage 14% 13% Global Macro -39% -20% Long/Short Equity Hedge 62% 71% Managed Futures -13% -22% Multi-Strategy 28% 44% Fund of Funds 26% 33% All Single Manager Funds 54% 62% *One-month ahead, 24-month rolling windows Slide 25

26 Hedge Funds Index Funds Sharpe Ratio: High Low Transparency: Low High Liquidity: Low High Risk Exposures: Complex Untapped New Simple Constraints: Few Investment Many Capacity: Limited Opportunities High Trading: Hyperactive Passive Fees: High Low Slide 26

27 Hedge Funds Index Funds Sharpe Ratio: High Low Transparency: Low High Liquidity: Low High Risk Exposures: Complex Simple Constraints: Few Many Capacity: Limited High Trading: Hyperactive Passive Fees: High Low Slide 27

28 These Ideas Are Not New Artificial intelligence and active management are not at odds with indexation, but instead imply a more sophisticated set of indexes and portfolio management policies for the typical investor, something each of us can look forward to, perhaps within the next decade. Andrew W. Lo, Journal of Indexes Q2, 2001 Slide 28

29 Conclusion Hedge fund dynamics are more complex Global economy is truly global, e.g., China, India Governments and central banks are now more active, e.g., QE and Volcker Technology has changed market dynamics, e.g., HFT, algorithmic trading, cybersecurity, fintech Liquidity has become more dynamic Adaptive Markets framework with active risk management Slide 29

30 Thank You! Happy Birthday

Adaptive Markets: Financial Evolution at the Speed of Thought

Adaptive Markets: Financial Evolution at the Speed of Thought Andrew W. Lo, MIT National Bank of Belgium and 11 Universities Finance Seminar November 29, 2017 29 Nov 2017 Slide 2 29 Nov 2017 Slide 3 Markets