Speaker 1: Bloomberg Audio Studios, podcasts, radio news.
Speaker 2: The most profitable hedge fund strategy of last year was
Speaker 2: buying something a lot of people don't like thinking about
Speaker 2: cat bonds. They have, unfortunately nothing to do with cats.
Speaker 2: In this case, cat is short for catastrophe, and cat
Speaker 2: bonds are for extreme weather events.
Speaker 1: Cat bonds are only four very rare, very catastrophic events,
Speaker 1: whether it's California quakes or even a Japanese tsunami.
Speaker 2: We talked about them with Gautam Nike, a Bloomberg reporter
Speaker 2: and editor based in London.
Speaker 1: The way it works is that if a defined event
Speaker 1: doesn't occur, then the investor they get to keep their
Speaker 1: money and they get paid a very handsome risk premium.
Speaker 1: If that catastrophe as defined does occur, they can lose
Speaker 1: some of their money or all of the money. So
Speaker 1: it's a big risk and it's a gamble against mother Nature.
Speaker 2: Gautum told us that while these bonds have been around
Speaker 2: since the nineteen nineties, they've been growing in popularity recently.
Speaker 2: A record sixteen billion dollars in cat bonds were issued
Speaker 2: in twenty twenty three, bringing the total market value to
Speaker 2: forty five billion today. On the show how cat bonds
Speaker 2: went from a niche corner of the financial world to
Speaker 2: becoming one of the market's hottest items, and how the
Speaker 2: increasing risks from climate change might complicate that. This is
Speaker 2: the big take from Bloomberg News. I'm Sarah Holder, So Gadam,
Speaker 2: how do catastrophe bonds work?
Speaker 1: So what catastrophe bond is a specialized form of insurance.
Speaker 1: So typically an insurance company would issue a cat bond
Speaker 1: if it didn't want to take on the risk of
Speaker 1: a Katrina like event occurring and destroying tens of thousands
Speaker 1: of homes and leaving the insurer on the hook for
Speaker 1: a huge amount of money. So cat bond is a
Speaker 1: way to pass on this risk to Wall Street, which
Speaker 1: is not traditionally part of the insurance industry.
Speaker 2: Catastrophe bonds are usually held for three to five years,
Speaker 2: and Gatham says the length is set that way for
Speaker 2: a reason.
Speaker 1: So it's not for ten, fifteen, twenty years that would
Speaker 1: be a huge risk. It's for a very narrow specific timeframe.
Speaker 2: But even in that specific timeframe, weather is notoriously hard
Speaker 2: to predict. Have you ever used a weather app So
Speaker 2: Gautam wanted to understand how the people buying these bonds
Speaker 2: were deciding which disasters to bet against. And when it
Speaker 2: comes to cat bonds, there's no firm that's bought more
Speaker 2: of them than for Matt's Capital Management. So Gadam went
Speaker 2: to Connecticut to visit them.
Speaker 1: So, you know, a typical hedge fund might have I
Speaker 1: don't know, marble floors and expensive art hanging in the
Speaker 1: on the walls, and you know, might be located in
Speaker 1: central Manhattan. But Fermat is quite different. You know, it's
Speaker 1: based in a pretty affluent town of Westport and Connecticut,
Speaker 1: but it's on a fairly modest street and opposite a
Speaker 1: car repair shop. If you enter the offices of Fermat,
Speaker 1: you know, you basically find meteorology and weather journals, a
Speaker 1: lot of wonky literature. In the reception area, you have
Speaker 1: a lot of white boards where equations and physics details
Speaker 1: are scrawled.
Speaker 2: At the center of all these whiteboards is John so For,
Speaker 2: Matt's co founder and managing director.
Speaker 1: He has a background in biophysics, and I think he's
Speaker 1: really used that scientific and mathematical acumen to good stead
Speaker 1: and sort of created his own models and his own
Speaker 1: mathematical techniques.
Speaker 2: One of Soo's earliest finance jobs involved creating unique derivatives
Speaker 2: to cover seemingly random events.
Speaker 1: So, for example, you know a charity that was organizing
Speaker 1: a golf tournament and would give somebody a car. If
Speaker 1: someone hit a hole in one, what is the likelihood
Speaker 1: of that hole in one occurring? And if it does occur,
Speaker 1: the charity might be wiped out. They'd be on the
Speaker 1: hook for you know, losing the car or prize money.
Speaker 1: So you would want to buy insurance against that happening.
Speaker 1: So he would calculate that kind of risk and create
Speaker 1: a derivative product that would you know, protect the charity
Speaker 1: and get someone did hit that hole in one.
Speaker 2: So told Gautam that when he started from matt with
Speaker 2: his brother in two thousand and one, he set out
Speaker 2: to build a science based model that would weigh the
Speaker 2: probability of a natural disaster against the returns on a
Speaker 2: cat bond. And his method starts with gathering a a
Speaker 2: bunch of meteorological data.
Speaker 1: There are specialized companies that take a lot of the
Speaker 1: meteorological data and crunch it and they come up with
Speaker 1: sort of a magic number what is the estimated loss
Speaker 1: of a particular event. So let's say a California earthquake.
Speaker 1: What is the likelihood that a particular earthquake could occur
Speaker 1: in a particular year in a particular area of California
Speaker 1: where there are a lot of expensive homes. Well, you'd
Speaker 1: have to know your plate tectonics, you have to understand
Speaker 1: the history of earthquakes. You'll have to look at the
Speaker 1: data that shows who has built homes in which area.
Speaker 1: And there are specialized companies that provide this kind of information.
Speaker 1: So what John so does is he buys these models
Speaker 1: from these companies, but then he does his own calculation.
Speaker 1: On top of that, he adds his own magic source
Speaker 1: to refine it so that he can sort of beat
Speaker 1: the capond market and perhaps beat other investors.
Speaker 2: And this magic sauce includes more unconventional methods like watching
Speaker 2: hours of film of California wildfires to understand where they're
Speaker 2: happening and how they're spreading, anything that might help refine
Speaker 2: the data coming in. And that also includes a model
Speaker 2: that has made for Matt's betting approach unique, one that
Speaker 2: borrows from out of all things airplane physics.
Speaker 1: He plotted one curve, which was the probability of a
Speaker 1: catastrophe against the potential losses. And then he plotted another
Speaker 1: line which showed how much profit he could make at
Speaker 1: different levels of risk. And when he put those two
Speaker 1: together on a piece of paper, they looked like the
Speaker 1: cross section of a wing. Once he realized, WHOA, this
Speaker 1: is just like a wing of an airplane. I can
Speaker 1: look at the physics of lift to compute the risk
Speaker 1: and reward at every point on those curves, and once
Speaker 1: you calculate that, you have a slightly better idea, quite
Speaker 1: a better idea of whether to invest in a particular
Speaker 1: set of bonds or not.
Speaker 2: But like other cat bond investors, a key part of
Speaker 2: Sow's strategy is to diversify. For Matt's bonds cover properties
Speaker 2: from Florida to New Zealand.
Speaker 1: So typical hedge fund would buy one hundred or two
Speaker 1: hundred different cat bonds. One would be save for a
Speaker 1: typhoon in the Philippines. What would be against a tsunami
Speaker 1: occurring in Japan. One would be against a wildfire in California. Now,
Speaker 1: the likelihood statistical likelihood of several of those natural disasters
Speaker 1: which are down to Mother Nature, really they're pure luck, right,
Speaker 1: The chances of those occurring in the same year are
Speaker 1: very very low. So even if one or two or
Speaker 1: three get triggered, these investors have positions in a whole
Speaker 1: bunch of other cat owns that don't get treated, so
Speaker 1: they don't lose money on those.
Speaker 2: For Matt So has taken catbond trading to the next level.
Speaker 2: The company accounts for a quarter of the entire cat
Speaker 2: bond market and had returns around twenty percent in twenty
Speaker 2: twenty three. That's way higher than the average eight percent
Speaker 2: returns brought in by the rest of the hedge fund market,
Speaker 2: and So is really confident in his calculations here he
Speaker 2: is on Bloomberg TV.
Speaker 1: Is the market or cat bron prices a better predictor
Speaker 1: of where hurricanes might make landfall or perhaps the kind
Speaker 1: of damage they may cause? Then an outfit like the NAA, Right,
Speaker 1: I think that there as good a predictor as you're
Speaker 1: going to get.
Speaker 2: After the break. What happens when the disasters cat bond
Speaker 2: traders are betting against get more unpredictable. Hey, we're back.
Speaker 2: Before the break. We were talking with Gautum Nike about
Speaker 2: catastrophe bonds and the man at the center of the
Speaker 2: firm that owns the most of them, John So. With
Speaker 2: the weather getting more unpredictable and extreme, I wanted to
Speaker 2: know what does that mean for So's models. Gadam says,
Speaker 2: So's calculations are some of the best in the industry,
Speaker 2: but they aren't bulletproof.
Speaker 1: You know, when Hurricane Katrina hit, his portfolio lost three percent,
Speaker 1: So he has his down years. You know, if there's
Speaker 1: a big catastrophe and he's holding cap bonds linked to that,
Speaker 1: he will suffer a hit just like any other investor.
Speaker 2: And Gautam says the way some cat bonds are structured
Speaker 2: also means that investors can be on the hook for
Speaker 2: less rare weather events what are called secondary perils.
Speaker 1: You have a lot more mid size natural disasters, so flooding, wildfires, tornadoes,
Speaker 1: and thunderstorms. Very often an insurance company will take a
Speaker 1: hurricane and package it with secondary I'll say, here's a
Speaker 1: cat bond. It covers a hurricane, but also covers floods,
Speaker 1: and it also covers wildfires. So as an investor, if
Speaker 1: you buy this cat bond, you know about the earthquake stuff,
Speaker 1: you're quite confident you have got to handle on the
Speaker 1: risk there. But the stuff on floods, the stuff on
Speaker 1: wildfire you have much less certainty about. So when you
Speaker 1: take on that cat bond, when you buy it, you're
Speaker 1: taking on risk you don't fully understand.
Speaker 2: So instead of predicting Hurricane Katrina, so it could be
Speaker 2: predicting a thunderstorm in New York City.
Speaker 1: That's right exactly.
Speaker 2: So my last question, katim if so has a better
Speaker 2: model to predict these natural disasters or the risk levels
Speaker 2: of these natural disasters using a lot of data and
Speaker 2: a lot of know how and technical expertise. This seems
Speaker 2: like information that governments and cities might want and that
Speaker 2: residents might want. It could save lives, help people anticipate
Speaker 2: devastating losses. Is buying and selling cat bonds really the
Speaker 2: the best are the only use case for his risk model?
Speaker 1: I think that I would say that cat bonds provide
Speaker 1: a very important service in that they help ensure people
Speaker 1: against catastrophic risk when traditional methods of protecting you, such
Speaker 1: as insurance, aren't available. Last year, less than one third
Speaker 1: of the three hundred and eighty billion dollars in global
Speaker 1: climate losses was covered by insurance. So the developing world,
Speaker 1: per countries we know, really at high risk from catastrophic
Speaker 1: events driven by climate change. They have very little insurance,
Speaker 1: but a CAT bond could provide that. So the World
Speaker 1: Bank right now has about a billion dollars an issued
Speaker 1: outstanding cat bonds for poorer countries, and it expects to
Speaker 1: increase that to about five billion. So I think CAT
Speaker 1: bonds will increasingly play a role in helping to sort
Speaker 1: of bridge that gap a little bit.
Speaker 2: This is the Big Take from Bloomberg News. I'm Sarah Holder.
Speaker 2: This episode was produced by Adriana Tapia. It was edited
Speaker 2: by Caitlin Kenny and Sharon Chen. It was mixed by
Speaker 2: Ben O'Brien. It was fact checked by Naomi. Our senior
Speaker 2: producers are Naomi Shavin and Elizabeth Ponso. Nicole Beemsterbor is
Speaker 2: our executive producer. Sage Bauman is our head of podcasts.
Speaker 2: Thanks for listening. Please follow and review The Big Take
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