A Ronald N. Kahn D Global Head of Systematic Equity Research, BlackRock M A S T E Alternative Data and R - Machine Learning in S Active Management T A M Global Interdependence Center Conference
La Jolla, CA
February 3, 2020
FOR USE WITH THE GLOBAL INTERDEPENDENCE CENTER CONFERENCE- PROPRIETARY AND CONFIDENTIAL
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A Big data and active management D M Recent Headlines • Is Big Data the Key to Bigger Investment Returns? A –Morningstar, March 2018 S • Will BlackRock’s Algorithms Beat the Fund Managers? T –Financial Times, March 2018 • The Rise of Machine Learning in Asset Management E –Yale School of Management, October 2018 R • Asset Managers’ Survival to Rely on Big Data Prowess, - Technology –Bloomberg Intelligence, October 2019 S This explosion of available data, along with the T analytical developments of machine-learning, A constitute the greatest new opportunity for M active management in many years. AEH0120U-1071665-8/9 FOR USE WITH THE GLOBAL INTERDEPENDENCE CENTER CONFERENCE- PROPRIETARY AND CONFIDENTIAL
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A Drivers of Success in Active Management D Opportunity M • Excess volatility (Shiller, 1981) A Key Sources of Active Returns • “Broad and Persistent” / Static S – Risk Premia (Ross, 1976): T – Behavioral anomalies (Kahneman and Tversky, 1979) • “Narrow and Transient” / Dynamic E – Informational Inefficiencies (Grossman and Stiglitz, 1980) R • Other: – Investor constraints - – Occasional opportunistic trading S T A M Source: The Future of Investment Management, Kahn (2018). For illustrative purposes only.
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A Decomposition of Active Returns D M A S T E R S T A M
Investment Return
Cap-weighted Index Benchmark Return
Rough attribution of key drivers:
Active Return
Return from Average (Static) Exposures to Smart Betas
“Pure Alpha” Return
Risk Premia Behavioral Anomalies
Informational Advantages
Source: BlackRock, as of January 27, 2020. For illustrative purposes only. AEH0120U-1071665-3/9 FOR USE WITH THE GLOBAL INTERDEPENDENCE CENTER CONFERENCE- PROPRIETARY AND CONFIDENTIAL
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Fr a c t io n o f M a n a g e r s in e a c h B u c ke t
A What Fraction of Active Returns Are Smart Beta? D M A S T E R S T A M 208 U.S. Active Equity Managers Mean = 31%
35%
30%
25%
20%
15%
10%
5%
0%
5%
10%
20%
30%
40%
50%
60%
70%
Percent of Active Risk Budget Explained by Factors
Data Source: eVestment. Analysis by BlackRock. Date as of 9/30/2019. 208 strategies classified in US Large Cap Core Universe by eVestment Alliance and benchmarked against S&P 500. R-squared statistic calculated from regression of monthly outperformance vs benchmark over 5year period October 2014 – September 2019, against monthly returns to Fama-French 5 factors. For illustrative purposes only. AEH0120U-1071665-4/9 FOR USE WITH THE GLOBAL INTERDEPENDENCE CENTER CONFERENCE- PROPRIETARY AND CONFIDENTIAL
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A Alternative data and pure alpha D In 1985, being able to access and process b/p ratios for every S&P M 500 stock was an edge. A Standard financial data now available in a timely fashion for S everyone with an internet connection. T Beyond that, we have seen an E explosion of data so vast that access isn't sufficient—effective R analysis is an edge. S T A M For illustrative purposes only.
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A D M A S T E R S T A M
Big data
Less structured Larger in volume Higher in frequency Digital traces of human behavior. Examples include: • Text, emails, filings, broker reports, conference call transcripts • Internet search activity • Social media: Twitter, Facebook, Google+, LinkedIn • Images • Video
Source: BlackRock 2020. For illustrative purposes only.
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A Machine Learning D Algorithms that learn and make predictions using data. M The technology used to analyze alternative/unstructured data A Very little of this is new (i.e. developed in the past 5 years) S T E R For my team, our success over the past ten years has been driven more by big data than machine learning. For the next ten years, machine learning may in fact be the - larger driver. S T A M • What is new is the amount of data and available computing power
• The challenges for investing are low signal-to-noise, non-stationarity, and relatively small amounts of data. • Compare that to image recognition, perhaps the greatest triumph of machine learning to date.
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A Important Notes D M A S T E R S T A M
THE INFORMATION CONTAINED HEREIN MAY BE PROPRIETARY IN NATURE AND HAS BEEN PROVIDED TO THE RECIPIENT ON A CONFIDENTIAL BASIS, AND MAY NOT BE REPRODUCED, COPIED OR DISTRIBUTED WITHOUT THE PRIOR CONSENT OF BLACKROCK, INC. ("BLACKROCK"). These materials are not an advertisement and are not intended for public use or dissemination. This communication and its content represent confidential information. This material has been prepared for informational purposes only, and is not intended to provide, and should not be relied on for, accounting, legal or tax advice. You should consult your tax or legal adviser regarding such matters. These materials are neither an offer to sell nor a solicitation of any offer to buy shares in any fund. You may not rely upon these materials in evaluating the merits of investing in any fund that employs any of the strategies referred to herein. Any reference herein to any security and/or a particular issuer shall not constitute a recommendation to buy or sell, offer to buy, offer to sell, or a solicitation of an offer to buy or sell any such securities issued by such issuer. This material is not intended to provide investment advice. BlackRock does not guarantee the suitability or potential value of any particular investment. Investing involves risk, including possible loss of principal. Past performance is not a guarantee or a reliable indicator of future results. Index returns are for illustrative purposes only. Index performance returns do not reflect any management fees, transaction costs or expenses. Indexes are unmanaged and one cannot invest directly in an index This material is not intended to be relied upon as a forecast, research or investment advice, and is not a recommendation, offer or solicitation to buy or sell any securities or to adopt any investment strategy. The opinions expressed may change as subsequent conditions vary. The information and opinions contained in this material are derived from proprietary and nonproprietary sources deemed by BlackRock to be reliable, are not necessarily all inclusive and are not guaranteed as to accuracy. There is no guarantee that any of these views will come to pass. Reliance upon information in this material is at the sole discretion of the reader. This material may contain "forward-looking" information that is not purely historical in nature. Such information may include, among other things, projections, forecasts, estimates of yields or returns, and proposed or expected portfolio composition. Moreover, where certain historical performance information of other investment vehicles or composite accounts managed by BlackRock, Inc. and/or its subsidiaries (together, "BlackRock") has been included in this material, such performance information is presented by way of example only. No representation is made that the performance presented will be achieved, or that every assumption made in achieving, calculating or presenting either the forward-looking information or the historical performance information herein has been considered or stated in preparing this material. Any changes to assumptions that may have been made in preparing this material could have a material impact on the investment returns that are presented herein by way of example. THIS MATERIAL IS HIGHLY CONFIDENTIAL AND IS NOT TO BE REPRODUCED OR DISTRIBUTED TO PERSONS OTHER THAN THE RECIPIENT. Š 2020 BlackRock, Inc. All rights reserved. BLACKROCK is a registered trademarks of BlackRock, Inc. All other trademarks are the AEH0120U-1071665-9/9 FOR USE WITH INTERDEPENDENCE CENTER CONFERENCEPROPRIETARY AND CONFIDENTIAL property of their respective owners. FORTHE USEGLOBAL WITH INVESTMENT PROFESSIONALS ONLY - PROPRIETARY AND CONFIDENTIAL
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