During Preston and Stig’s interview with legendary investor, Edward Thorp, he provided the recommendation that the hosts should read the book Superforecasting, by Philip Tetlock and Dan Gardner.  Based on that recommendation, we have provided a chapter for chapter overview in this podcast on the art and science of predictions.

According to The Wall Street JournalSuperforecasting is “The most important book on decision making since Daniel Kahneman‘s “Thinking, Fast and Slow.”  The Harvard Business Review paired it to the book The Power of Mathematical Thinking by Jordan Ellenberg.  Regardless of other peoples’ opinions, we found the book to be quite interesting and useful for value investors.  The book does a great job of teaching the reader the importance of understanding cognitive biases and also trying to use a balanced state of mind to conduct assessments on how things might behave in the future.

In this episode, you’ll learn:

  • The right framework for making correct forecasts
  • How to prevent confirmation bias for your investments
  • Why financial experts are storytellers rather than forecasters
  • How and why the best investors constantly change their opinion

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Summary of Superforecasting

If you would like to download the below summary of Superforecasting in .pdf format, follow the link.

Chapter 1: An Optimistic Skeptic

Whether you’re buying a house or stocks, or whether you’re getting married or changing your job, you’re predicting something or the other to an extent. It’s just our basic nature, and while some people who claim to be experts are marginally better at it than an average random guesser, others are really good at it. Tetlock conducted a research on forecasting, and although his findings pointed out as to why some people can predict better than the others, it was grossly misinterpreted.

Today, we seek the opinions of forecasters on many events including sports, yet when it comes to important areas such as our finance, we completely ignore these forecasters. Accurate prediction is now more important than ever, but the irony is that though current scientists have much better access to information than their peers, they are still no closer to accurate predictability. At the end of it all, there are limits, even when it comes to predictions, but it would be futile to dismiss all predictions as useless information. For instance, you might be able to find correct predictions of the weather tomorrow, but are you sure that it’s going to be accurate if taken for a week? What about a month later? Basically, anything can happen and predictions depend on the circumstances to a large extent. There’s no way we can really know, but the least we can do is try.

Chapter 2: Illusions of Knowledge

When a doctor or any expert in the medical field tells you that you’re suffering from something, you blindly believe it. And, why wouldn’t you? After all, the expert is supposed to be perfect and error-free, right? Wrong. Today, physicians prescribe medications even if they aren’t sure about it. Take the example of Archie Cochrane who was told by his doctor that he had a terminal illness. The doctor didn’t even wait for the reports but confidently stated that he had cancer. Mr. Cochrane, just like his doctor, didn’t question his doctor’s judgment, and the doctor was so confident about himself that he didn’t bother to check the facts.

The field of medicine has been riddled with problems even before the twentieth century where there were no evidence that their treatments actually worked. Doctors are not exempt to any human biases, so it becomes difficult to discover knowledge for them. In fact, you won’t be blamed if you believe that it’s best to let diseases take their natural course rather than relying on physicians since some prescriptions are really dangerous. Doctors suffer from illusions of knowledge, but they aren’t the only ones to blame since biases are rampant in other areas including politics and sports.

Chapter 3: Keeping Score

When Steve Ballmer from Microsoft predicted that the iPhone would never garner significant shares, he had no idea that he would be devastatingly wrong. Not only did the iPhone rock the tech world, but it also makes more revenue than entire Microsoft! How’s that for a wrong prediction?! But, in Steve’s defense, remember that he said “significant” and there’s no way to measure it exactly. Also, Ballmer never mentioned what “market” he was referring to. Therefore, although his name is etched in the hall of shame when it comes to absurd predictions, we still can’t say that he’s wrong.

Similarly, many pundits throw ambiguous statements so that it gives them some room to wiggle out when proven wrong. As it is unpleasant and embarrassing to be wrong, many people optimize to prevent mistakes. Truth be told, it’s good to be wrong because you learn more, but most people don’t think that way. So, what makes a good prediction? Well, any statement that’s unambiguous, probabilistic, and confident with specific numbers can be taken seriously. Sure, there’s still a chance that one could go wrong, but it’s better than making a fool out of yourself.

Chapter 4: Superforecasters

When faced with tough questions, most people substitute the tough question with an easier one and answer it. Once done, they genuinely believe that they have successfully answered the tough question. This theme of baiting and then switching is very popular but dangerous at the same time. Imagine a game of poker for example. While a beginner can overestimate her cards and bet big, her actions aren’t considered wise even if she gets lucky and wins. On the other hand, a seasoned player can get unlucky and lose even if he has made the right bet. Good investors and players think the same way. They recognize skill because that’s one factor that can improve their judgments over time.

In essence, good forecasters develop the ability to question things. If the Intelligence Community had questioned its decision before raiding Iraq, they would never have been embarrassed. Like physicians, they didn’t even entertain the possibility that they could be wrong. Needless to say, someone may not be right or wrong, but not questioning their assumptions can be devastating.

Chapter 5: Supersmart?

During Tetlock’s research, he met several superforecasters who had gathered as volunteers. Although they were all from different fields, they had several things in common – highly educated with excellent numerical capabilities, voracious readers, intelligent, and broad knowledge in several fields. It’s plausible to think that the superforecasters are better than average people mostly because of their intelligence; however, plausibility is never enough, and Tetlock’s research was all about testing it.

To take the research a step further, regular forecasters and superforecasters were compared with common people. While the regular guys scored 70 percent more in intelligence, superforecasters displayed 80 percent. With just a 10 percent gap, one can conclude that superforecasters are no doubt intelligent, but they aren’t geniuses either. Therefore, you don’t need fancy PhDs to become a superforecaster. Superforecasting doesn’t demand raw intelligence, but what’s more important is that you use it.

Chapter 6: Superquants?

Forecasting sometimes has a cloud of uncertainty over it, and superforecasters acknowledge that. It’s almost impossible to know something for sure, and as shown in the movie Zero Dark Thirty, the intelligence analysts were also uncertain about Osama’s whereabouts. Of course, the movie highlights a confident heroine where she’s a hundred percent sure about Osama, but reality is not that simple. Superforecasters are aware of uncertainties, but their confidence also plays a major role here.

For example, think about financial advisors. People usually trust confident advisors faster when compared to advisors who are less confident. In fact, accuracy and confidence may seem different, but they are correlated. But, as humans, we place so much confidence in this correlation that we exaggerate it unintentionally. This is why some less confident superforecasters aren’t trusted even if they are accurate. History shows that we have always struggled with probability, and whether it is politics or sports, this bias is rampant everywhere.

Chapter 7: Supernewsjunkies?

So, what makes the difference between a superforecaster and a regular forecaster? We already know that superforecasters are slightly more intelligent than regular forecasters, but is that all? Also, while others suffer from biases like belief perseverance – being very resistant to any updates or new information once they have made up their mind – superforecasters tend to update themselves with information and also change their decisions when something new comes up.

Superforecasters value fresh evidence even if it means that their previous prediction could be wrong. Belief perseverance can be harmful, especially if you’re trying to predict something, and it can be impossible to sway you if your beliefs are fixed. Generally, it occurs when they are closer to your identity. However, what puts superforecasters apart from regular forecasters is that they know how to distinguish between irrelevant and relevant information. Irrelevant information has the power to weaken your confidence even if you have all the evidence in front of you and this is known as the dilution effect.

Chapter 8: Perpetual Beta

Another important factor that makes superforecasters different is that they possess the growth mindset. Growth mindset is all about believing that you can learn and grow more to your fullest extent. People with fixed mindsets often come up with excuses and rarely find success. However, people with growth mindsets, like the superforecasters, believe that practice can make them better.

Practice indeed makes man perfect. When Tetlock conducted a test, the superforecasters did better than forecasters who had also practiced. How did that happen? Well, it all boils down to effective practice. In essence, practice becomes mighty and effective only if you’re certain about what you’re doing. But, it also demands additional requirements such as timely feedback. Feedback helps you, sure, but what good is it if it’s not on time? Not only does slow feedback hamper your progress but it offers fewer opportunities even if you want to correct your mistakes. The financial industry suffers from this problem where feedback is often poor, and therefore, it doesn’t make them better than common laymen in any manner.

Chapter 9: Superteams

President Kennedy’s administration was full of twists and turns as people remember the Bay of Pigs tragedy even today. While the White House faced criticism worldwide for this debacle, the team performed brilliantly under extreme pressure during the Cuban missile calamity. One would think that Kennedy fired all his team members and started afresh; however, that’s not true. Kennedy went ahead with the same team, but the members who had acted foolishly previously had now averted one of the biggest crises ever. So, what really happened?

Kennedy’s team consisted of great performers, but they had more than a few problems. The group members were so comfortable with each other that they rarely raised concerns. They constantly agreed with one another and since everyone was on the same page, they assumed that they were on the right path. When Kennedy insisted on a thorough investigation to identify where they went wrong, it was obvious that their unanimity was the biggest problem. Therefore, Kennedy changed the rules a bit. Skepticism became their new mantra and group members were instructed to take charge as experts in their own fields. They were also given all the rights to question others and that’s where the changes began to take place.

Similarly, when forecasters form groups, they are advised to stop thinking as a group. They are encouraged to be confrontational in a healthy manner and this brings out all the troubled areas to the forefront, which enables them to understand how they can improve themselves.

Chapter 10: The Leader’s Dilemma

It’s a universal fact that leaders are recognized by three key characters – confidence, decisiveness and a vision. Forecasting can be very beneficial to leaders, so they are definitely interested to become superforecasters. However, when you look at the qualities of a superforecaster, how well does it match with a leader? Forecasting comes embroiled in uncertainties, and if a leader is uncertain, how can he expect to lead others? So, can an individual become a leader and a forecaster as well? You may not think so, but yes, it’s possible.

In fact, the superforecaster model can help leaders become better at their roles and also make their teams more effective. Take the example of Moltke – a Prussian general who led his country to victory by tweaking a few things. Moltke knew that nothing was certain, and instead of barking orders to his people, he communicated effectively. This encouraged his people to take better decisions without having to wait for their superiors. Also, Moltke allowed unceratinities when it came to certain situations, but he was never uncertain about his decisions. Similarly, leaders can lead their team by encouraging them to question things and take decision

Chapter 11: Are They Really So Super?

Tetlock always conversed with Daniel Kahneman – the psychologist who won the Nobel Prize – during his research. Tetlock asserted that what made the superforecasters stand apart from regular people is their attention to detail. Superforecasters put in a lot of hard work, think through things carefully, listen to their own and others’ perspectives, update everything regularly, and then arrive at conclusions. Also, superforecasters use their System 2 to catch any mistakes committed by System 1.

Yes, superforecasters are indeed spectacular, but all this can be extremely exhausting, and Kahneman was confident that humans can’t avoid biases completely. However, Tetlock argued that humans can prevent biases in specific situations. Both Tetlock and Kahneman tested various subjects and several researchers and scientists also gave their inputs. While Nassim Taleb argued that forecasting isn’t all that useful since nobody could even imagine the Black Swan events, Tetlock assures that it is possible to imagine and prepare for such events.

Chapter 12: What’s Next?

In a nutshell, forecasting has many advantages, but the biggest impediment standing in the way of accurate forecasting often stems from the forecasters themselves. This is because as a human, the forecaster puts his personal interests ahead of the task ahead. In other words, instead of seeking the truth, the forecaster sometimes becomes blindsided. However, the good news is that many industries are now adopting the superforecaster model. Of course, there was a lot of opposition, but many countries are now embracing evidence-based policies, and this extends to medicine as well. Forecasting may appear like a game to some, but it’s very real; in fact, the stakes are actually high and substantial. Good forecasting can always make the difference between bankruptcy and prosperity in business, and when it comes to national security it also has the potential to predict about wars. Accurate forecasting is always in demand, and if the forecaster can follow all the commandments, he is on his way to

Of course, there was a lot of opposition, but many countries are now embracing evidence-based policies, and this extends to medicine as well. Forecasting may appear like a game to some, but it’s very real; in fact, the stakes are actually high and substantial. Good forecasting can always make the difference between bankruptcy and prosperity in business, and when it comes to national security it also has the potential to predict about wars. Accurate forecasting is always in demand, and if the forecaster can follow all the commandments, he is on his way to becoming a superforecaster.

Books and Resources Mentioned in this Podcast

Dan Gardner and Philip Tetlock’s book, Superforcasting – Read reviews of this book

Preston, and Stig’s interview with investing legend Ed Thorp

Preston and Stig’s interview with well-renown value investor Guy Spier

Preston and Stig’s interview with Dr. Robert Cialdini

Preston and Stig’s discussion on Nassim Taleb’s book The Black Swan


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