Survey
* Your assessment is very important for improving the workof artificial intelligence, which forms the content of this project
* Your assessment is very important for improving the workof artificial intelligence, which forms the content of this project
Behavioral Biases And Governance How To Avoid Being Your Own Worst Enemy 1 Peter D. Gerlings, CFA, CAIA Copyright © 2015 by The Segal Group, Inc. All rights reserved. Introduction “When everyone thinks alike, everyone is likely to be wrong.” – Neill “I find more and more that it is well to be on the side of the minority, since it is always the more intelligent.” – Goethe “The trouble with the world is that the stupid are cocksure and the intelligent are full of doubt.” – Bertrand Russell “Everyone has a plan until I hit them.” – Mike Tyson • Humans are hard-wired to make bad investment decisions – Behavioral Biases – Governance Pressures • Meanwhile, managing portfolios has become more complicated than ever – – – – • Time horizon compression Accelerating change Sheer number of choices Information deluge How can investors cope? – Examples – Recommendations Have You Seen These Behaviors? • DC Plan Participants – – – – – – – Spend little time planning for retirement Don’t monitor their investments Don’t optimize voluntary contributions Under-choose target date funds Under-select annuities Over-react to the latest economic report Few participants access the substantial resources available about: • Financial goal setting • Investment alternatives • Tax strategies • Smart consumer practices • Investment Committees – – – – Believe that committee members and participants consistently make decisions rationally and with relative competence Try to educate participants while conveying a neutral point of view and thereby under-emphasize intelligent choices Focus on “how we did lately” and “what is the near term investment outlook” Make investment picks by glancing in the rear view mirror and relying on charisma Behavioral Biases Versus Optimal Investment Decision Making • Premises – Human beings have a profound tendency towards making unprofitable investment decisions – The nature of governance can amplify poor decision making tendencies – All investment decisions involve some combination of • Rational thinking • Mental shortcuts • Emotion – The world is becoming more complex • And at an accelerating pace • There is an arms race between investment complexity and fiduciary bandwidth Behavioral Biases Versus Optimal Investment Decision Making • Premises – Retirement plan participants may make more sub-optimal decisions, but members of investment committees and their advisors are also human – Organizations can impart their own biases on decision making – The operating model of a committee should be structured to mitigate sub-optimal decision-making resulting from behavioral and organizational biases Our Goals – To explore some of the challenges and potential pitfalls faced by investment committee and individual investors alike – Introduce techniques from behavioral economics and finance which can help improve investment outcomes – Offer suggestions for next steps Human Behavior Biases • We Are Hard Wired To Make Poor Investment Decisions – However, profitable investment decisions are not impossible to make – And behavioral biases are not impossible to surmount – The first challenge it to be aware of these biases and how they affect everyone • The brain is a truly remarkable thing – Especially when thought of as a “pattern recognition device” • No computer comes close to its amazing speed and accuracy • (Some programmers are determined to try, however) – Unfortunately, the brain doesn’t know what it doesn’t know • And can form spurious relationships • And hold on to cherished myths Human Behavior Biases $6.00 A manifestation of how the brain acts like a pattern recognition device is called “linear extrapolationism” – The tendency to project forward indefinitely the trend we observe today $5.50 $5.00 $4.50 $4.00 Manager (Projected Returns in Blue) $3.50 $3.00 Manager (Actual Returns) Before an investment $2.50 $2.00 $1.50 After an investment decision $1.00 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 • Human Behavior Biases • Linear Extrapolation Bias – Our brains really want to extend trend-lines indefinitely into the future • It’s why securities’ prices vary far in excess of what’s suggested by their underlying fundamentals • Bubbles and their painful crashes are manifestations of this phenomenon • As a species, we never seem to learn • Confirmation Bias – Seek out information that supports existing views – Discounts information which conflicts with existing views Human Behavior Biases • Attribution Error – Assigning positive motivations and/or attributes to our group • “But officer, I was speeding because I’m late for something really important!” – Negative motivations and/or attributes to those outside our group • “Hey – that jerk is speeding! I hope he gets a ticket!” – Closely related to false confidence • “Everyone is stupid but me” Human Behavior Biases • Bias towards the Status Quo – “5 Monkeys, a banana and a fire hose” • Creates enormous inertia • Often irrational • Groupthink – Herd mentality • “Everyone has to be like Yale” • Peer group obsession – Better to fail conventionally than succeed unconventionally – “No one ever got fired for hiring IBM” – “None of us is as dumb as all of us” Human Behavior Biases • Bias Bias – “Every has biases but me” – Dunning-Kruger Effect – the inverse relationship between how much we actually know about something, versus how much we think we think we know about it Governance • Governance is a Human Construct – And is therefore subject to Human biases, and especially • Appeals to authority • Group think – But in addition, there are the following challenges: • Living in a fishbowl – Decisions are often second guessed by people with » Less experience » Less relevant knowledge – College/University Endowments are particularly impacted by this » Student advocacy » Various outside constituents • Career risk management – Someone else might be doing your job if you’re not “careful” Governance • The Impact of Behavioral Biases and Governance Pressures leads many investors to – Buy high and sell low • Occurs at both the manager and the asset class level – Are typically invested in only after they have gone up in value – Are typically divested from only after they have gone down in value • The excuses always sound the same – “Look how good they appeared when we made the decision to hire them!” – “How could I have possibly known they would eventually underperform?” – Made worse by the “No one ever got fired for hiring IBM” phenomenon • Significant value is destroyed during the manager search process – Majority of asset managers underperform after they have been selected – Majority of asset managers outperform after they have been terminated Governance • The Impact of Behavioral Biases and Governance Pressures leads many investors to – Follow the herd • Clustering around certain asset classes, managers • Made much worse by “Horse Race” mentality – Everyone “must” be in the top quartile – Individual circumstances (liquidity needs, time horizons, etc.) too often ignored when comparing results • Made worse still by the “Cocktail Party” effect – People like to brag about their investments – It’s no fun watching your neighbor make more many than you do – But also overestimate their own capabilities • Especially relative to third-party options (agency/principal bias) • Be overly optimistic Increasing Complexity • • Apart from all the biases discussed earlier, investors today are confronted by increasing complexity And not only are investments MUCH more complicated than they were – The rate of change is accelerating • Explosion of information – Human knowledge doubles every 7 years – It feels linear when we look at history, but in fact it is geometric going forward • Think of the movie “Back to the Future” – It was made in 1985 – Marty McFly went back to 1955 – The pace of advancement between 2015 and 1985 is arguably greater than between 1955 and 1985 » » » Smart phones Internet GPS Increasing Complexity • 1980s and earlier – – – – Balanced Portfolios Mostly U.S. focused Relatively few managers (sometimes only 1!) Quarterly (sometimes just annual) reporting Increasing Complexity • 1990s-2000s – Asset class specialization • • • • • • • U.S. Equities U.S. Bonds Foreign Equities Foreign Bonds Tactical Asset Allocation Real Estate Alternative Assets – – Private Equity Hedge Funds • Many more managers, sometimes dozens Increasing Complexity • 2010s and beyond – – – – – – – Smart Beta Infrastructure Liquid Alternatives Tail-risk management Overlay strategies Etc. Lots and lots of managers Increasing Complexity • The future? – Hard to predict, but it seems reasonable to expect • • • • More complexity More information to process More compressed decision making No guarantee that there will be more time and resources with which to manage all this complexity Increasing Complexity • In a way, we have gone full circle – Back in the 1980s • Most endowments and foundations were 100% outsourced – Local bank trust department – Maybe a few external asset managers – In the 1990s, asset class specialization put decisions back into investors’ hands • Asset allocation • Manager selection • Rebalancing Increasing Complexity • The trend towards complexity has only accelerated into 2015 – Style specialization – Direct hedge fund investing – Tactical risk/rebalancing tools • We’re back to having many decisions made by investment committees – But often without appropriate resources and/or training – And often unable to keep up with accelerating change Example: Manager Selection Problem Which Manager Would You Pick? Manager A Manager B Assets Under Management $20 Billion $7.2 Million Clients Over 100, including sophisticated investors and well-known families 11 Doctors Results Average annual 10 years of 25%; volatility 2%/year Average annual 6 years of 25%; volatility 14%/year Portfolio Basket of S&P 100 stocks with options strategy 30-40 stocks Offices New York and London Omaha, Nebraska Answer Manager A Manager B Bernie Madoff Warren Buffett Examples of Bias and Response • • Annualized Returns Recency Bias LastQ YTD 1 Yr. 3 Yr. 5 Yr. 10 Yr. Small Cap Growth (Gross) 16.7% 28.0% 29.1% 24.7% 12.6% 14.4% Small Cap Growth (Net) 16.5% 27.5% 28.2% 23.8% 11.8% 12.8% Russell 2000 Growth Index 3.7% 17.4% 23.7% 20.0% 8.9% 9.6% Solution: Avoid the “hot dot”; avoid “lucky idiots” at all costs Hot Dots Versus Future Performance • Assume you can pick between portfolios – Portfolio A - Up 20% over the last year – Portfolio B - Down 20% over the last year – Which portfolio would you expect to do better over the NEXT 12 months? • Assuming that there is anything less than 100% turnover in both portfolios – All other things being equal, Portfolio B now has more attractive valuation characteristics than Portfolio A – Over the long run, valuation matters (It should be said that there are LOT of factors which influence future performance, and many are simply unknowable in advance. However, the impact of recent performance on relative valuation is too often ignored.) Examples of Bias and Response • Choice Paralysis: “Let’s give both managers money.” • Solution: Establish a disciplined set of criteria with a scorecard Examples of Bias and Response • Optimism Bias: “We can select winners after four 30-minute presentations.” • Solution – Revisit process and past results – Do a governance checkup Examples of Bias and Response • Bias Towards Herding – Chasing investments made by other funds – Amplified when investors are considered “sophisticated” – Investments considered attractive, even though they may not meet the specific and unique circumstances for that investor • Solution – Consider each investments potential on your unique circumstances – How does it impact my liquidity? Time Horizon? Risk Profile? Examples of Bias and Response • Bias Blind Spot: “Sure, a lot of people let these things get in their way, but not us.” • Solution: Team building exercises Suggestions for Investment Committees Creating High Performing Teams Form Committees with Diverse Perspectives Conduct Periodic Training on Bias Avoidance and Framing Effects Align Advisors’ Framings with Investment Policy Execute an Operating Model Designed to Avoid Making Suboptimal Decisions Suggestions for Investment Committees • Experiencing Behavioral Bias First Hand • Informative Research and Applications for Your Business • Reflecting on Past Committee Biases • Planning: Revise the Committee Operating Model Applied to Key Activities • Availability Heuristic • Comparative Competence • Complexity Aversion • Confirmation Bias • Endowment Effect • Familiarity Bias • Gambler’s Fallacy • Groupthink Bias • Halo Effect • Hindsight Bias • Loss Aversion • Mental Accounting • Narrative Fallacy • Optimism Bias • Outcome Bias • Probability Neglect • Recency Bias • Regressive v. Exaggeration Biases • Risk Aversion and Risk Seeking Biases • Sample Size Neglect Bias • Status Quo Bias • Sunk Cost Curriculum Human Biases Creating High Performing Teams •Selecting Investment Options •Selecting Defaults •Communicating Fund Options to Participants •Offering Participant Education Sessions •Revisiting the Investment Policy Statement •Reviewing Fund Performance •Rebalancing the Portfolio •Evaluating Proposals •Checking References Summary: How to Manage All This • Despite the complicated (and possibly bleak) picture painted so far, there is hope for investors – Awareness of our biases is an important first step • Not all can be completely overcome (and remember “bias bias”) • But if we’re aware of our bad tendencies, we can work to mitigate their impact – There are groups out there (including Segal Rogerscasey) that can help with governance issues • Fiduciary outsourcing • Committee education/training • Improved communications/analytics – The trick is to optimize the combination of internal resources and external resources Thank You