Frodo Risk

FRODO RISK PART 1 – THE EYE OF SAURON, RECESSION PREDICTION AND MY BI-ANNUAL SYSTEMIC RISK REPORT

I’m a big science fiction and fantasy fan and one of the towering works of the genre is J.R.R. Tolkein’s The Lord of the Rings. At its heart the story is about the battle between good and evil pitching a fragile alliance of men, elves and dwarves against the rising powers of evil led by Sauron and his orcs of Mordor. Sauron does not have a physical body but rather takes the form of a great, all-seeing eye perched on top of a tower in Mordor, the so-called Eye of Sauron.

He is forced to take this form because he was actually killed many thousands of years before but had managed to survive on by tying his life force to the ‘one ring.’ This ‘one ring’ is paradoxically both the source of his strength but also the eventual tool of his destructive. Frodo Baggins, the most unlikely of heroes being just a hobbit from the Shire, takes the ‘one ring’ and after a terrible journey across Middle Earth manages to destroy the it in Mount Doom and with it Sauron himself.

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The story is instructive I think because it has similarities with the recent recession. Sauron, I’m sure knew that he would die if the ‘one ring’ was destroyed and therefore should have considered all the ways that this might happen, despite the fact it would have seemed very unlikely. In fact, knowing that the ‘one ring’ could only be destroyed in Mount Doom he should have started with the ‘one ring’s’ destruction and worked backwards to consider all the possible scenarios that this highly unlikely event might happen and crucially what the tell-tell signs leading up to the event might be because oftentimes you can only see something if you are actively looking for it. Returning to the recent recession, although of course econometrics, statistical programs and economic modelling are all very powerful tools they do have the very obvious drawback that they fundamentally work by assuming that the future will look like the past therefore all it takes to lead them astray is the historically unprecedented! I believe that econometrics modelling should be complemented with what I like to call ‘Frodo Risk’ analysis.

Bi-annual report

My idea then is for a bi-annual report that would be bought by investors to give them a systematic overview of the world economy and possible causes of systemic risk. It would only be bi-annual because a) the report would likely take a long time to prepare and b) investors do not have that much time to be constantly reading updated research. Ultimately the aim is to help highlight possible long-term build-ups of systemic risk and so the limited frequency I think would not be a problem. It is important the report would, at least attempt to, be systematic because I think one problem with a lot of current macroeconomics research is it feels like in-depth journalism. However, much like how the ‘eye of Sauron’ can be distracted from seeing Frodo, I believe sometimes journalism can be distracted from seeing the build-up of systemic risk by the latest hot topic.

The report would be divided into 100+ mini analyses. These would be structured thus:

Obvious categories of potential systemic risk to consider would be: ‘asset class bubbles’ ‘war/terrorism’ ‘environmental/weather/global warming’ ‘natural resources, energy crises’ ‘inequality, democratic political unrest’ ‘debt’ ‘bankruptcy of major companies’

Conclusion

In just writing that small piece on a potential bubble in American University education I already find myself being forced to think hard about issues that otherwise I might not. I think a report of a 100+ or so of these potential causes could realistically hope to, within that hundred, catch any major cause of global economic systemic risk. For the potential investor therefore to, on a bi-annual basis, read a report on all these potential causes would, I think, help very much in first offering alternative perspectives on their portfolio’s risk profile and second possibly inspiring their own research into a specific asset class etc.


FRODO RISK PART 2 – RESEARCH FIRM

[Michael Burry’s] got Asperger’s syndrome which makes him even more interesting because in fact it ties him back to the other characters. All the characters are in one way or another socially cutoff, isolated either by volition or by syndrome. And as a result they are not hearing the signals, they are not hearing the same music that you and I would, ‘they’re looking at data’ ‘they’re looking at data or they are filtering it through their own peculiar imaginations. But they aren’t part of the Wall Street social world. And in some way or another they are not hearing the propaganda. Asperger’s syndrome is not a bad metaphor for what it was about them, this isolation, this self-isolation’ ‘uncomfortable in social situations’ ‘or didn’t like them.’ Michael Lewis in an interview with Charlie Rose on his book The Big Short and the people who correctly predicted the 2007 sub-prime Financial Crisis.

This essay is a follow-up to my previous article on ‘Frodo Risk.’ In that essay I argue that the problem with statistical approaches is that they rely upon the assumption that the future, at least in some way, mirrors the past. This assumption leaves them exposed to the historically unprecedented. Much like how Sauron, the evil leader of Mordor from the Lord of the Rings, fails to predict (and prevent) Frodo Baggins from destroying the one ring in Mount Doom I believe that standard macroeconomic modelling approaches fail to predict recessions because recessions usually have some element of the historically unprecedented. It is like the famous quote that ‘generals always fight the last war.’

It should be emphasized that the failure of macroeconomic modelling is not partial but total. I recently read an article written in 2012 by IMF economist Prakash Loungani in which he points to the astonishingly appalling record that economists have in predicting recessions.

In 2000, I wrote in the Financial Times that “the record of failure to predict recessions is virtually unblemished.” A dozen years and many recessions later, there is little reason to change my assessment. My initial conclusion was based on my findings that only two of the 60 recessions that occurred around the world during the 1990s were predicted by private sector forecasters a year in advance. About 40 of the 60 recessions remained undetected seven months before they occurred. As even as late as two months before each recession began, about a quarter of the forecasts still predicted positive growth for the country concerned. With my colleagues Jair Rodriguez and Hites Ahir, I’ve since looked at the record of forecasting recessions over the decade of the 2000s and during the Great Recession of 2007-09. Let’s consider the 2000s first and restrict attention to forecasts for twelve [sic] large economies—the G7 plus the ‘E7’ (emerging market economies–Brazil, China, India, Korea, Mexico, Russia and Turkey), which together account for over three-quarters of world GDP. There were a total of 26 recessions in this set of countries. Only two recessions were predicted a year in advance and one of those predictions came toward the turn of the year. Requiring recessions to be predicted a year ahead may seem like an unreasonably high bar to set.

This should be incredibly surprising. After all, alongside delivering sustained economic growth, the most important contribution macroeconomics could make to society would be the prevention and eradication of recessions from our economies. Failing that, macroeconomics should at least be able to deliver long-term, accurate prediction but as we have just seen from the Loungani article this is not the case. Some would argue that economics is just too complicated, human systems are just too complex, which I concede they just may be. But I still think it is fascinating to note that in no other area of human endeavour have you had so much raw brain power, human expertise and competitive incentive systems (academia and finance) and yet had so much failure.

My solution to this problem of predicting recessions is to start with imagining all the possible causes of systemic risk, with the guiding principal of: if it is big just imagine what would happen if it would go bad? Then with this list of hundreds of potential ‘Frodo Risks’ you would then try to work backwards and crucially figure out what would be the tell-tell signs that the imagined crisis is slowly developing. Finally you would then track all of these hundreds of potential ‘Frodo risks’ and try to spot potentially systemic threats as they develop. Of course, underpinning this approach is the idea that recessions are long-term predictable which again I concede they may not be. The timing issue is interesting, and my initial idea about how to guess the time of when the market cottons on is to track FT or Economist articles about the issue and correlate an uptick there with a market wide understanding.

WHAT WOULD THE IDEAL SYSTEMIC RISK RESEARCH FIRM LOOK LIKE?

Culture/mentality

There are four guiding principals to my idealized systemic risk research firm.

The first is that you cannot see something unless you are actively looking for it. I think this is especially true in economics where any coherent economic model will almost always have plausible explanations for whatever is occurring. In fact, the standard economic modelling approach of current equilbrium + trend + exogenous shocks makes it very easy for long-run build ups (for example in leverage) to be justified because well look it’s only slightly higher than it was six months ago and six months ago it was perfectly fine!

The second is the value of the outsider, someone who isn’t hearing the music. The problem is how to acquire a detailed understanding of something and yet not become indoctrinated into that way of thinking. One of the advantages that outsiders have is that they can risk asking the stupid beginner questions that an expert cannot because it could potentially reveal an embarrassing lack of basic understanding. I would also add that being an outsider is not just in the sense of a specific industry but also in terms of personality. If you think about most of the examples of people who saw the housing bubble as profiled in Michael Lewis’ ‘The Big Short’ and Gregory Zuckerman’s ‘The Greatest Trade Ever’ many of them had serious social problems. The best example of this is probably Michael Burry who has Asperger’s syndrome and a full suite of personality quirks. In most of working life, particularly in big corporations, eccentricities are punished and it tends to be the socialized and like-able that rise to positions of power and influence. When it comes to something like economics research though the hiring preferences can and should be a little different.

The third is that creativity, as suggested by Steven Johnson in his book ‘Where Good Ideas Come From’, is largely a function of diverse influences bashing together. Therefore to be more creative you need to proactively expose yourself and your ideas to a diverse range of influences.

The fourth is the importance of what Robert Greene in his book Mastery calls negative capability. This is the ability to be comfortable with not immediately understanding something. This is the idea of not giving in to the need to have an opinion about everything but instead continuing to wrestle and play with the idea. In my own small way, many of my best and most status quo challenging ideas have come only after months of mulling them over. John Cleese, of Monty Python made the same point when he gave a lecture on creativity

Well, let me tell you a story. I was always intrigued that one of my Monty Python colleagues who seemed to be (to me) more talented than I was {but} did never produce scripts as original as mine. And I watched for some time and then I began to see why. If he was faced with a problem, and fairly soon saw a solution, he was inclined to take it. Even though (I think) he knew the solution was not very original. Whereas if I was in the same situation, although I was sorely tempted to take the easy way out, and finish by 5 o’clock, I just couldn’t. I’d sit there with the problem for another hour-and-a-quarter, and by sticking at it would, in the end, almost always come up with something more original. It was that simple. My work was more creative than his simply because I was prepared to stick with the problem longer.

Work practices

To produce a bi-annual report the working year would be broken into two six month parts. There would be a 5 week break over Christmas and an 7 week break over Summer. This would allow every six months for twenty weeks of working time to produce a report. This would be a sizable increase in holiday time compared to a typical employee which I think would offset the relative inflexibility of when people can take their holidays. One major advantage of such long holidays is that I think it would allow people to spend part of the year living in different countries. I watched a TED talk with the founder of a prestigious design firm who every seven years closed down the firm for a year to allow him and his staff to have a year sabbatical and be exposed to new influences. Clearly an economics research firm cannot just take a year off but I think it could valuably benefit from the long holidays.

Each 20 week block would be divided into 10 fortnight working weeks where the team would work from Monday of week 1 and through the weekend to Tuesday of week 2 to make 9 straight days of working. This would be finished with five days of weekend. The value in this I think is proper recovery from the working week in a way that I think it is harder to do with just two days of rest every seven. Hopefully by having five days of rest per fortnight as opposed to the normal four people will be more willing to switch. I also think the five days could realistically be used for short holidays around the world which, I know myself in particular, would love to take advantage of to go and visit all the friends I have dotted around. The 9 days of work would be demanding with long twelve hour days starting at 8am and finishing at 8pm. The exception would be the working weekend where finishing at 5pm would allow employees to not completely lose their weekend every other week. You would probably allow for an additional three of four days in each six month period so people can have at least some flexibility with the working year. Of course, a lot of people would not be willing to work like this but I think given that research firms are very small and only need to be about ten people this should not be a problem. Additionally I think being different has the optimal advantage of helping keep people feeling like an outsider and not tied to the system.

It is really important to have a lot of exposure to diverse influences so every day there would be three hours allocated to reading time, maybe from 11am to 1pm just before lunch and another hour in the afternoon. This would be supplemented by perhaps one afternoon per fortnight where employees could work on essays and develop ideas of their own choosing (much like Google’s 20% time). All this reading would help give employees a regular diet of different influences and the opportunity to develop new insights. Perhaps to create a diverse team of researchers peoples’ reading and interests might be tracked in an effort to maintain diversity and breadth in thinking. Clearly, although there would be a heavy bias away from fiction towards non-fiction and academic literature, you would want to allow the reading to be as varied as possible. Warren Buffett of Berkshire Hathaway said that

I insist on a lot of time being spent, almost every day, to just sit and think. That is very uncommon in American business. I read and think. So I do more reading and thinking, and make less impulse decisions than most people in business. I do it because I like this kind of life.”

Charlie Munger, Buffett’s partner at Berkshire Hathaway said something similar

In my whole life, I have known no wise people who didn’t read all the time – none, zero. You’d be amazed at how much Warren reads – at how much I read. My children laugh at me. They think I’m a book with a couple of legs sticking out.

Everyday there would be a team lunch at 1pm for an hour and a half where people can get closer and exchange ideas. In general I think I would probably be against having regular formal meetings because I believe that having to defend ideas that challenge the status quo in their nascent stages is very counter-productive as ideas (especially early on) are inherently very fragile, even to the lightest questioning. Nonetheless eating together and the more informal conversation that would involve would not only bring a family atmosphere but could also be a good way to share ideas and create diverse influences. You might even want to occasionally allow members of the research team to give mini presentations about books they have read or topics that interest them. Afterwards there would be the option of a thirty minute nap which would allow for biphasic sleep patterns which help people recharge for the afternoon and also reduce people’s daily total sleep time.

The optimal pay structure is interesting I think. My initial gut reaction was to tie pay to the performance of the firm. So have a low minimal wage at say £30,000 a year with additional % of profit to all the employees. I think the problem with this is it incentivizes high sales not good research. So my initial idea would be to keep records of the Frodo risk rating and how well they correlate with actual events and then reward accordingly. This would create very long-term incentives tied to getting the answer right.

Finally, I think I would ultimately opt in favour of diverse influences over sectoral expertise. Therefore researchers would every six months be, probably randomly, allocated different clusters of potential systemic risks to work with the view that that would keep our thinking fresh and hopefully insightful. You might even offer each researcher, perhaps once or twice a decade, a chance to spend six months just reading, thinking and writing about whatever they want: a sabbatical in the office if you will.

Office

I think big financial organisations and universities make it harder for people to think creatively because they, through their big impressive buildings, implicitly intimidate their employees into accepting the status quo. This is to me very similar to how banks would try and give confidence to their customers by having big expensive buildings. Therefore I think the office should be in a non-financial district. My current thinking is a cool converted art studio in east London somewhere.

For the team lunch there would need to be a big open table to eat together and I also think it would be good to have an office library stocked with books and kindles.

Over time it might be beneficial to develop a suite of internal literature on what major schools of thought. Maybe even Munger-like checklists as a ward against human misjudgement. One of my favourites would be on any analysis a section on ‘what would convince me that I’m wrong?’ as well as internal quotas on criticisms of other peoples work and why they may be wrong.

Team

I am a big fan of Michael Lewis’ Moneyball which is a book about how the baseball team the Oakland A’s which had one of the lowest wage-bills in the MLB managed to compete with the big expensive teams like the New York Yankees by taking advantage of the mispricing of player value. I similarly believe that these same mispricings occur in the labour market for economics researchers. There are a number of biases I would try and take advantage of in my hiring decisions.

Firstly, there is a bias in favour of well-rounded, socialized and generally pleasant people. These are all great qualities in friends but not necessarily in out of the box researchers.

Secondly, I think there is bias discriminating against those who have had unconventional or volatile academic and professional careers. I think it makes more sense to judge a person’s ability to do good research not by their consistency but by their highs. As an example John Paulson who’s hedge fund, as profiled in Gregory Zuckerman’s ‘The Greatest Trade Ever’ made $20 billion dollars in the Great Recession, had an analyst on his team called Paolo Pelligrini. In fact it was Pelligrini who was responsible for making the shorting sub-prime trade recommendation. Pelligrini had an exceptional academic career where he came in the top 5% at Harvard and where one of his Maths professors said he was one of the most gifted students he had ever come across. His professional career, marred by poor client skills and disagreements with bosses, meant that I think he is a classic example of an undervalued asset. In fact, Ben Horowitz of venture capital firm Andreessen Horowitz talks about how Marc Andreessen is very difficult to work with and at times can be, frankly, a bit of a prick. Andreessen it is worth mentioning is a Silicon Valley legend who co-authored the first internet browser and was co-founder of Netscape. Horowitz’s point is that in normal working life you would not put up with these types of people as it would disrupt team culture but because creating disruptive companies is so hard what matters is exceptional genius and you should be willing to accept even very extreme personality flaws to get it.

‘I’ll take strength over lack of weakness every day… This isn’t WalMart or something; to do something new that is going to be the best in the world you need greatness.’ Ben Horowitz

Similarly, predicting economic recessions is probably the hardest thing you can do in economics so you should be willing to trade-off likeability for genius.

Thirdly, I think there should be an effort to employ a true diversity of people. Not just across different academic backgrounds and cultures but personality types as well. Despite the incredible (and commendable) racial diversity at most major corporations I still believe there is a striking monochromatic feel to modern corporate culture.

Fourthly, if every six months you had advisers come in on short-term contracts to offer their perspectives I think this would really help freshen up our thinking. You might eventually even want to have several small offices around the world and rotate staff to really mix up the influences on our thinking.

Fifth, have someone in the firm who regularly thinks about every person in the office and how they probably feel about their career. Are they excited? Do they feel listened to? Do they feel like they are important? Is there anything we can do to make their lives better? And then try and make office policies to improve things. I think this would be especially do-able if you have a small team of people.

I’ll finish with some parting words from Charlie Munger

It’s my opinion that anybody with a high I.Q. who graduated in economics ought to be able to sit down and write a ten page synthesis of all these ideas that’s quite persuasive. And I would bet a lot of money that I could give this test in practically every economics department in the country and get a perfectly lousy bunch or synthesis. They’d give me Ronald Coase. They’d talk about transactions costs. They’d click off a little something that their professors gave them and spit it back. But in terms of really understanding how it all fits together, I would confidently predict that most people couldn’t do it very well. By the way, if any of you want to try and do this, go ahead. I think you’ll find it hard. In this connection, one of the interesting things that I want to mention is that Max, Planck, the great Nobel laureate who found Planck’s constant, tried once to do economics. He gave it up. Now why did Max Planck, one of the smartest people who ever lived, give up economics? The answer, he said, “It’s too hard. The best solution you can get is messy and uncertain.” It didn’t satisfy Planck’s craving for order, so he gave it up. And if Max Planck early on realized he was never going to get perfect order, I will confidently predict that all of the rest of you are going to have the same result.

In fact, when Charlie Munger was asked in 2010, in a lecture at the University of Michigan, about his views on the economy the first thing he said was

Well let me start with a qualification. Warren and I have not made our way in life by making successful macroeconomic predictions and betting on our conclusions. Our system is to swim as competently as we can and sometimes the tide will be with us and sometimes it will be against us but by and large we don’t much bother with trying to predict the tides because we plan to play the game for a very long time. I recommend to all of you exactly the same attitude. It’s kind of a sneer and a delusion to outguess macroeconomic cycles. Very few people can do it successfully and some of them do it by accident. When the game is that tough why not adopt the other system of swimming as competently as you can and figure that over a long life you’ll have your share of good tides and bad tides.


FRODO RISK PART 3 – CATEGORIES OF RECESSION

Peter Thiel likes to ask the question ‘what valuable company is nobody building?’ and the more I think about the more I think this Frodo Risk company is one of them. It’s been less than a month since I wrote my first article about Frodo Risk as a concept and I can’t really remember where I got the idea from but already it just has that feeling of ‘this makes so much sense, why is nobody doing it?’ Part of the problem is that it’s very difficult to execute. In particular you are trying to be simultaneously systematic and comprehensive about ultimately unknowable future events. My initial best guesses on how to do this will be the focus of this article.

CATEGORIES OF RECESSION/SYSTEMIC RISK

Political Uncertainty – e.g. Eurozone crisis, Iranian Revolution 1980s, US September 11th, 1997 Asian Financial crisis

Asset price bubbles – e.g. 2008 US Housing crisis, dot-com bubble early 2000s, US 1857 railroads bubble

Fiscal tightening – e.g. US 1937-38

Monetary policy/Interest rate – e.g. 1980 US,

Market collapse – e.g. US 1836-38 Cotton market

Bank failures – e.g. US 1836-38

Cost-push (particularly energy) – e.g. 1973-74 US oil crisis, 2007-08 food prices

High leverage – e.g. 2008 US Housing crisis,

Post-war – e.g. US 1920-21

Lack of technological progress – e.g. Peter Thiel argument is bubbles form if no better alternative e.g. 2008 US Housing, Early 2000s tech bubble

Big company – e.g. 1926-27 Henry Ford switched production from Model T to Model A closing factories for 6 months, US 1873 – failure of Jay Cooke & Company, 1857 US Ohio Life Insurance & Trust company failure

Other country – e.g. 1980s Iranian Revolution, US 1847-48 because of British Financial Crisis

FINAL THOUGHTS

Even if you set a low bar of predicting 1 year in advance just 25% of the recessions that occur (according to IMF economist Prakash Loungani the market 1 year in advance predicts about 5% of the time), spotting recessions is an awesomely difficult task.

Clearly there are some shocks that are going to be beyond a few researchers in a room e.g. terrorism or natural disasters. Nonetheless I think comprehensive monitoring of asset price bubbles, government fiscal/monetary tightening and failure of one big company/market leading to general uncertainty are all situations that could be mapped out in advance with reasonable predictive power.

Of course the whole challenge is for any research firm trying to predict recessions crying wolf is just a big a sin as missing recessions. Ultimately the goal goes way beyond selling research to a few hedge funds, really you’d want the firm (or firms like it) to become so widely listened to that their research can move markets and recessions can not only be predicted but actually prevented. But that’s a dream for the future.