Dataset of Trillion Dollar figures
Below I link to a small dataset with 130 figures of over $1 trillion (e.g. Apple’s Market capitalization: $1 trillion, or the value of Global Residential Real Estate: $163 trillion).
If something costs trillions, then it might score highly on the scale criteria of some prioritization frameworks. This because even if we have to invest billions to somehow save that money, the savings would be huge.
These numbers might also be helpful to get a sense of the world economy. For instance, World GDP is ~$100 trillion, and more than half of that is US, China, and EU with a GDP of ~$20 trillion each.
Also, people sometimes treat big numbers—billions and trillions—as if they’re all the same (c.f. scale insensitivity or scope neglect). Even researchers sometimes confuse big numbers (“Advertising has become an over $500-trillion-dollar global industry” (should be billions) or “The benefits of automated and autonomous vehicles $1.3 quadrillion” (should be trillions)).
So how can you conceptualize $1 trillion? 1 trillion is 1,000 billion. 1 billion is 1,000 million. Houses often costs ~1 million. So 1 trillion ≈ 1 million houses—a whole city.
Some of the figures might be wrong. For instance, because I optimized for selecting very high figures (I had a Google Scholar alert for things like “USD * trillion”), they are more likely to be inflated than other numbers (c.f. optimizers curse).
Also note that not all of these figures are necessarily directly comparable (some figures are stock and some are flow, some of the large figures are notional).
I hope this is interesting or even useful to some people here.
Also like this idea! Confused about Moody’s revenue—it’s $1T? Is it not ~ $4.2BN with 12,000 employees (as opposed to 1,300)?
Nice, you found another blunder in the literature!
“First, and classically, rating agencies’ fees tend to be high. The revenues of rating agencies come from new ratings and from the reexamination of former ones, as it is very difficult for a company, once it has been rated, to withdraw its rating from the market. It means the operational risk of rating agencies is quite low, just as the volatility of their revenues. We don’t know much about the prices of ratings and the profits of agencies. Nevertheless, in 2011, the operational profit of Standard and Poor’s and Moody’s was about 40 %; and Fitch’s was 31 %. For the first nine months of 2011, the revenue of Standard and Poor’s reached US$ 1.3 trillion for about 1,400 analysts. The figures for Moody’s were US$ 1.2 trillion for 1,300 analysts. These figures make for an annual revenue per analyst higher than US$ 1 million, which is quite high.”
from this paper on reforming rating agencies: https://sci-hub.tw/https://link.springer.com/chapter/10.1007/978-3-319-44287-7_12
So this should be billions, not trillions.
I had actually interpreted the figure differently and thought that rating agencies analysts rate trillions in value or something.
Have deleted these from the dataset.
It is certainly amazing the the world nominal and PPP GDP are smaller than the Global Debt in the non financial sector, which is at the same time smaller than the Global Household Wealth. I am a bit confused: how can de GDP be smaller than the Global Household Wealth?
Wealth is accumulated money, while GDP is per year. Debt is also accumulated, while deficit is per year.
Why isn’t GDP also accumulated? I mean, GDP is wealth in any given year (perhaps discounting debt somehow?)
I think the term GDP by definition means in one year.
Like if someone asked me what my salary is, and I said “I have £10k in the bank!”, I wouldn’t be answering the question. I should say “My salary is £30k per year” or whatever it is. If someone asked about my wealth or net worth, then the amount I have saved would be relevant.
Interesting idea! It might be nice to embed the image, or maybe multiple images. If you don’t know how to do that, you can do that by uploading the image to imgur, writing a word like photo, selecting it then choosing the image icon. You can then resize the image by dragging it.
done! thanks for the suggestion
Interesting idea!
I notice that many of the largest numbers are derivative notionals. It is important to note that this is a totally irrelevant number; derivative notionals are essentially arbitrary up to a scalar multiple.
As an example, suppose you and I want to make a bet about overnight interest rates on the first day of 2021 - specifically we agree that I will pay you $1 for every 1% the Fed Funds overnight rate is above 2%, and you will pay me $1 for every 1% it is below 2%, capped at $2 either way. The way we would formalise this as a contract would be:
An interest rate swap with 2% rate, one day tenor and $36,500 notional.
A receiver swaption with a 4% strike, one day tenor and $36,500 notional.
A payer swaption with a 0% strike, one day tenor and $36,500 notional.
In total this is over $100,000 worth of notional… for a $2 bet! What matters is the economic exposure of the derivatives, but this can be hard for non-specialists to calculate, so people often substitute the easier but irrelevant question of gross notional. Unfortunately this can include regulations, which has caused a variety of problems in the market.
Separately, you list ‘global debt in the non-financial sector’ as $1,521 trillion, but the source provided suggests it is $152 trillion. I suspect your scraping tool may have mistaken a footnote for an order of magnitude.
Thanks—I fixed the global debt in the non-financial sector figure!
And yes, you’re right that notionals need to be interpreted carefully—I initially had a paragraph in my post that notionals should be interpreted carefully, but then I cut it out. Your example is a good one and shows that, in theory, a world with a high notional value of derivatives trading can be one with a stable financial system.
However, I disagree that it is a “totally irrelevant number” and that the in practise notional total volume might be (a not entirely very bad) proxy measure for economic stability.
See Wikipedia:
“To give an idea of the size of the derivative market, The Economist has reported that as of June 2011, the over-the-counter (OTC) derivatives market amounted to approximately $700 trillion, and the size of the market traded on exchanges totaled an additional $83 trillion.[9] For the fourth quarter 2017 the European Securities Market Authority estimated the size of European derivatives market at a size of €660 trillion with 74 million outstanding contracts.[10]
However, these are “notional” values, and some economists say that these aggregated values greatly exaggerate the market value and the true credit risk faced by the parties involved. For example, in 2010, while the aggregate of OTC derivatives exceeded $600 trillion, the value of the market was estimated to be much lower, at $21 trillion. The credit-risk equivalent of the derivative contracts was estimated at $3.3 trillion.[11]
Still, even these scaled-down figures represent huge amounts of money. For perspective, the budget for total expenditure of the United States government during 2012 was $3.5 trillion,[12] and the total current value of the U.S. stock market is an estimated $23 trillion.[13] Meanwhile, the world annual Gross Domestic Product is about $65 trillion.[14]
At least for one type of derivative, Credit Default Swaps (CDS), for which the inherent risk is considered high[by whom?], the higher, nominal value remains relevant. It was this type of derivative that investment magnate Warren Buffett referred to in his famous 2002 speech in which he warned against “financial weapons of mass destruction”.[15] CDS notional value in early 2012 amounted to $25.5 trillion, down from $55 trillion in 2008.[16]”