ARE YOU ASKING THE RIGHT QUESTIONS? At Home Richard Cantrell is a 48 year old institutional investment manager. His teenage daughter, Jessica, is going to a concert with her friends tonight. They are a large group so will be traveling in two cars, one driven by nineteen year old James and the other by his sixteen year old brother, Bobby. Naturally, Richard is concerned about his daughter’s safety, so he wants to be sure she will be in the car with the better driver. Luckily, the other kids are being dropped off at Richard’s house and the whole group will leave from there, giving him an opportunity to have a conversation with the brothers before she leaves.
James is home from college for the weekend. He’s a freshman studying finance at Richard’s alma mater and even joined his old fraternity. He’s driving a 5 year old Volvo that looks like it just came off the showroom floor. His younger brother, Bobby, isn’t sure which college he wants to attend. At the moment he’s more concerned about his new Ford Mustang which is going to the body shop tomorrow for repairs. Apparently, some old lady was’t paying attention when she backed out of her parking spot and clipped the back corner of his car. Neither of the boys has received a traffic violation, or at least neither was willing to admit it to Richard. They are both clean cut, well spoken and would never think to drink and drive. If it came to it, which “it most certainly will not”, they would call their father to pick them all up rather than drive while intoxicated.
Based on the information gleaned during his investigation, with whom would you have wanted your daughter to ride?
Well, James is older, making him a more experienced driver, not to mention he drives a car commonly associated with safety, which also happens to be in pristine condition. He is following the same life path as Richard, so naturally he assumes James is likely to approach other decisions in a similar way as well. Although it’s possible young Bobby is telling the truth about the old lady, Richard has yet to meet a teenager who ever thought anything was their fault, so he treats Bobby’s story with a grain of salt. Plus, Mustangs are muscle cars and we all know what type of driver is attracted to that kind of power. Richard is the analytical type. He doesn’t like to rush to judgment, but given the information available he would rather be safe than sorry, so despite her protests, he insists that his daughter ride with James, or not at all. She promised to abide by his wish.
Jessica kept her promise, but never made it home. On the way back from the concert, James ran a red light. An eighteen wheeler plowed into the passenger side of the Mustang, killing all four occupants. James’ blood alcohol level was nearly twice the legal limit.
Richard consoled himself with the knowledge that he had done all he could to keep his daughter safe. Given the information available, he had done the right thing. The problem is, Richard had fallen prey to numerous cognitive biases which, despite his best intentions and experience, undermined the entire decision making process and led to a fatal error. Let’s analyze Richard’s assessment to see what I mean.
Roughly 50,000 students from all walks of life currently attend Richard’s alma mater, and hundreds of thousands more attend schools that are nearly identical to it. In the years between the time when Richard graduated and today, millions have passed through that institution and the others like it. To assume James approached decisions in a similar way to Richard solely because of the institution he attended is far fetched, no matter how much it appeals to his, and our, intuition. James was home for vacation from school where his battered Camaro was parked that night. His parents, knowing James’ poor driving record, insisted that he drive their Volvo while he was home. That didn't sit well with James and so after "one or two beers" at the concert, he pressured his younger brother to swap cars for the ride home.
While James was sincere when he told Richard that he wouldn’t drive while intoxicated, unfortunately, James had a different definition of what it meant to be intoxicated. He truly believed he was “ok to drive”. In fact, like Richard, James also believed he was a better driver as a result of his 3 years behind the wheel (see chart). His overconfidence resulted in a more cavalier attitude toward the driving experience. So, unlike his younger brother who was still a cautious driver, James liked to drive with the music turned up loud and didn't think twice about other potential distractions caused by his passengers. James truly believed he was a good, responsible driver who was prepared for any situation. After all, he'd been driving successfully for three years, without a single fatality or even fender bender that he considered to be his fault. Responsible, because he always demanded that his passengers wear their seatbelts.
By now, you must be asking why I’ve shared this story with you. The answer is, because it is representative of the decision making process so pervasive in our industry, complete with all the usual cognitive biases, including framing, representativeness, the halo effect and availability. Consider the following.
At Work Frank Swanson is the Chief Investment Officer of a large endowment. He is a stickler for details. Before he will consider investing in a particular hedge fund they must pass a screening process based on a checklist of items which, over the course of many decades, have become generally accepted characteristics of the most successful investment managers. In addition, he relies on the intuition honed over his 25 years in the business. If something just doesn’t feel right to him, he will pass. It’s a process that has served him well, as evidenced by the fact that he now oversees $45 billion in diversified assets.
Today, Frank and his team are meeting with the leaders of two young hedge funds. The first, started by the former global head of foreign exchange and interest rate trading at a marquee investment firm where he had a reputation for making a lot of money, launched with $500 million in AuM. $50 million of it came from his own pocket. With three years under their belt, they haven’t knocked it out of the park, nor have they blown up. Like most established firms, they’ve experienced a few good runs with the occasional rough patch, but nothing which should raise alarm bells. They have 15 analysts, an economist who used to work at the Fed and another from the BOE, plus 10 portfolio managers with experience in a wide range of asset classes. They employ tight speed bumps to ensure no single PM can “do too much damage”, and in any case, the majority of risk is taken by the CIO. They use the most revered law firm, accountants, auditors, and fund administrators to handle their administrative and operational needs, and employ the most trusted risk management software which is overseen by an independent risk officer. The firm subscribes to the best known independent research and has direct access to thought leaders throughout the industry.
The other fund being assessed today is run by a man who has been a portfolio manager at three different hedge funds over the past 10 years. All three had failed for three different reasons, none of which appeared to be tied to his actions. Although he had produced excellent returns, his sharpe ratio was barely above 1.0. While he had run several very profitable trading units prior to moving to the buy-side, they were all within second-tier banks and insurance companies, so he isn’t well known throughout the industry. The firms who handle their legal, accounting, auditing, and administrative work are also well known and reputable. The CIO doesn’t believe in outsourcing research, trade structuring or execution, so he doesn't have any analysts, nor do they subscribe to outside research either. All ideas are internally generated by scouring economic and market data in the same manner that produced his track record, and goes a long way to explain why his returns are so uncorrelated to every major index. His fund currently has just $20 million in AuM, mostly from friends and family, but he has previously managed upward of $1 billion in his independent portfolios.
Based on the information gleaned during Frank’s investigation, with whom would you have invested?
If you are being honest, the clear winner is the first fund. Purely from a marketing and fund raising perspective, simply coming out of a prestigious firm, such as Goldman Sachs or Morgan Stanley, provides a distinct competitive advantage. That credibility translates into commitments from other credible institutions which creates a credibility cascade, resulting in the $500 million launch. With such a base, other large institutions with both minimum investment and maximum proportion rules in place can participate. Being familiar with the allocator “checklist”, the first manager catered to them all. Truth be told, he believed in the value of the checklist too which is why he didn’t hesitate to pull together so many analysts, economists and advisors.
As for the second fund manager, while he may have a more transparent and excellent track record, qualifying his accomplishments requires more work. He suffers from something akin to guilt by association. Although it is clear that he was not responsible for the downfall of the firms at which he had been employed, simply being associated with them created a mental hurdle that had to be overcome, Precisely the opposite of what the other manager had working in his favor.
Mistakes in Common Truth is, in both Richard’s analysis and Frank’s, there wasn’t any information provided that was of any predictive value. Every bit was meant to trigger bias in you, the reader, by appealing to our deep seated beliefs. Even the description of Frank conveyed little information of real value, yet it likely generated serious bias within the reader’s mind.
The analysis in both cases were perfunctory, at best. In neither case was any inquiry made regarding the decision making process of any of the participants. How did James arrive at his decision to attend Richard’s alma mater? Why did the first manager employ tight speed bumps? How did the second manager deliver such uncorrelated returns so consistently? How does James define intoxication in that moment? Would one beer qualify? Why did he select the Volvo? How much did the first manager’s group at his old employer make in the five years before he took over relative to what it made under his guidance? How about the three years since? Why employ speed bumps? Why would you (not) employ analysts? Questions which should have been asked were ignored, and in the absence of those answers, we filled in the missing pieces with bias.
When you understand how decisions should be made in order to generate better results over time, you have a better understanding of the questions that should be asked in order to better predict the performance of drivers, traders, portfolio managers, CIO’s and allocators. To do so requires fighting our natural inclination to achieve cognitive ease by relying on gut feel and intuition, in favor of inviting cognitive strain by asking questions that require deep reflection and investigation. Truth be told, the correlation between alpha generation and the information being used to make investment and allocation decisions by the majority of decision makers in this industry is highly speculative at best. Simply working at a highly regarded, very profitable investment firm is no more predictive of the ability to generate alpha as a hedge fund manager than attending your alma mater can predict a teenager’s ability to deliver your daughter home safely.
Learning Lessons from Cognitive Science One of the most fascinating discoveries to come out of the field of cognitive science is that, when faced with questions that are difficult to answer, our brains are prone to replacing them with alternative questions that would appear to be the same, but are easier to answer. Unfortunately, appearances can be very misleading, and potentially disastrous. Let’s review the following, first described in Seeds 15-24, as a prime example.
At a large oncology conference, a speaker presented the following facts to hundreds of practicing professionals in the audience:
1% of women at age forty who participate in a routine mammogram have breast cancer.
80% of women with breast cancer will receive positive mammograms.
9.6% of women without breast cancer will also get positive mammograms.
They then put the following question to the audience:
A woman in this age group had a positive mammography in a routine screening. What is the probability that she actually has breast cancer?
The average answer provided not only in this conference, but in four similar circumstances over the course of the following decade, was roughly 80%.
Without realizing it, this group of hundreds of very intelligent, highly educated professionals had replaced the difficult to answer question posed to them, with one that sounded almost identical. They had replaced, “What is the probability that a woman in this age group who had a positive mammography has breast cancer?” with, “What is the probability that a woman who has breast cancer will have a positive mammography?” While they may appear to be the same question, the answers are very different. The answer to the question posed is actually 7.8%, or less than 1/10th the probability.
Now, consider how different the conversation might be when an oncologist delivers the news to her patient if she believes that patient has an 80% chance of having breast cancer versus a 7.8% chance. Not to mention how different the prescribed course of action would be on the follow.
Both Richard and Frank made similar mistakes in trying to make their decisions, but they are mistakes made by so many others too. For instance, we might be interested in answering the question, “What’s the probability that a fund launched by a former partner at a prestigious investment firm will generate positive results over time?”, but replace it with the seemingly similar question, “What’s the probability that a fund launched by a former partner at a prestigious investment firm will raise significant AuM?” Drawing Conclusions The fact is, in spite of all the checklists, thousands of analysts, due diligence questionnaires, use of speed bumps and tight stops, risk management systems, impeccable CV’s and thorough investigations, the great majority of investment allocators rarely, if ever, beat the returns of the funds they invest in, and an even greater majority of investment managers rarely beat the indices of the assets in which they invest. In order to understand why that is, we must come to better understand the wiring of our brains and its natural predilection for answering the easy questions rather than pondering the difficult ones, and our tendency to go with what feels right versus what has been proven to be correct.
About the Author For nearly thirty years, Stephen Duneier has applied cognitive science to institutional investment management. The result has been career best returns for experienced portfolio managers who have adopted his methods, the turnaround of numerous global trading businesses, the development of an award-winning $1.25 billion dollar hedge fund and 20.3% average annualized returns as a global macro portfolio manager.
As a speaker, Stephen has delivered informative and inspirational talks to audiences around the world for more than 20 years on topics including global macro economic themes, how cognitive science can improve performance and the keys to living a more deliberate life. Each is delivered via highly entertaining stories that inevitably lead to further conversation, and ultimately, better results.
Stephen Duneier was formerly Global Head of Currency Option Trading at Bank of America and Managing Director of Emerging Markets at AIG International. His artwork has been featured in international publications and on television programs around the world, and is represented by the world renowned gallery, Sullivan Goss. He received his master's degree in finance and economics from New York University's Stern School of Business.
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