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pash

3,410 karma · joined May 28, 2011

I do quant-finance and ML things, write Haskell, and ride bicycles. I also do other things, but less often.
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pash··on Kraken Wins Bank Charter Approval
Sorry, re-reading my comment I can see that it is likely only to add to the confusion. (The downvotes suggest so also! Apologies all around.)

I meant to make two points. First, that IMO it is misleading to say that a bank simply creates new money ex nihilo when making a loan, counter to what you wrote ("the bank does not need to have $10k sourced from somewhere else"). There is in fact a bound on the amount of new lending a bank can undertake, one related to its assets, and in that sense the money lent does "come from somewhere." My attempt at a (poorly) stylized accounting was meant to illustrate what sort of thing makes up a bank's cash assets and how they relate to lending, but I'll try a new approach below. Second, I was trying to clarify what "bank money" means, to explain how it gets created, as much of the broader confusion in this thread seems to be around what "[bank] money-creation" really entails.

Let me try to make my first point again. In modern banking systems, fractional reserve has been mostly replaced by capital requirements, which limit a bank to holding an amount of (risk-weighted) assets no greater than some multiple of its capital. A bank's capital is its assets less its liabilities, which we'll write A - L. Let's call the regulatory capital multiple M, then capital requirements essentially say that A <= M(A - L). When a bank makes a new loan, its assets and liabilities increase equally in the way you described. That means that for a loan of X, if the lending bank is not already bounded by capital requirements, that the capital adequacy inequality becomes X + A < M(A + X - (L + X)) = M(A - L). That is, the left side of the inequality increases but the right side of the inequality is unchanged, so the capital requirement binds more tightly. In particular, it must be that the loan amount X < M(A - L) - A; in other words, new loans are constrained to be less than the excess of regulatory capital over pre-existing assets. So a bank cannot just create arbitrarily large new loans; loans are constrained by capital, the positive component of which is assets. That's where loan money "comes from": a bank's assets.

The second point I meant to make about bank money-creation was not directed at your comment specifically. But I wanted to point out that "bank money" simply means the sum of all bank deposits, and that it, too, is constrained to be a finite number. In this sense also banks cannot poof into existence arbitrarily large loans (with corresponding deposits) in the way I read your comment to imply.

pash··on Kraken Wins Bank Charter Approval
> If you apply for a $10k loan from a bank then, once the loan is approved, the bank will simultaneously:

- increase your current account balance by $10k (credit your current account) - increase your loan account balance by $10k (debit your loan account)

That $10k deposit appeared from nowhere. You didn't 'put the deposit in', and it wasn't transferred from another customer or another bank. And the bank does not need to have $10k sourced from somewhere else.

This is not correct. A bank lends against its cash assets, not against nothing.

Bank accounting works like so: when you deposit $1 at the bank, the bank’s assets increase by $1 (the $1 you just gave it), and its liabilities also increase by $1 (the bank owes you your dollar back when you want it). A bank’s loans are financed by its assets; each dollar it lends is a dollar taken from the asset side of its balance sheet. When a bank lends you $1, it (1) decrements its asset balance by $1, (2) increments your bank account by $1, (3) creates a new asset representing a $1 loan on its own balance sheet, and (4) creates a new liability for you representing a loan of $1 owed.

Point is, a bank does not create money from absolutely nothing when making loans in the way you describe. All loans are financed by the bank’s assets, and a bank cannot originate a larger value of loans than the value of its cash assets. Bank “money-creation” refers to the fact that the total bank account balances in the economy increase when a bank makes a loan; this happens after what I described in the previous paragraph, since the $1 loan now increments your bank account, while nobody else’s bank account balance decreases.

(To see how this works in more detail, imagine the process begins with Alice depositing a one-dollar bill at the bank, and then the bank loaning Bob one dollar. Keep track of the distinction between who has the one-dollar bill and who has a one-dollar bank account balance. The loan proceeds as follows: first the bank gives Bob the one-dollar bill it took from Alice as a deposit, then Bob turns right around and deposits the one-dollar bill back at the bank. The result is that Alice and Bob now both have $1 bank account balances after the loan is made, whereas only Alice did before; the bank still has the one-dollar bill. Summing either bank account balances alone or balances plus dollar bills shows $1 more after the loan was made.)

pash··on Topology Illustrated (2015)
Topology is a canonical example of "mathematics without numbers" (and indeed of "qualitative" rather than "quantitative" mathematics), so for anyone approaching it with an undergrad or lesser background in math, learning it feels a bit like starting with a clean slate. As benrbray mentions in a sibling comment, there aren't any prerequisites in the usual sense, as you won't need to draw on any reserve of mathematical facts built up in learning previous topics while studying it. But learning it does require the ability to assimilate axioms (and to intuit why they make sense as a starting point), and then the ability to reason about those axioms rigorously to draw out the interesting consequences.

That said, a background in some mathematical topics is useful for learning topology. The subject is rooted in a particularly abstract notion of distance, so it's useful to have some experience reasoning with somewhat less abstract notations of distance like metrics, the most familiar of which is the quite numerical Euclidean metric involving the familiar square root of the sum of squares. Familiarity with metric spaces in general (that is, spaces equipped with any axiomatically acceptable notion of a metric distance) is even more useful because it requires a similar sort of axiomatic reasoning as does topology.

Kolmogorov & Fomin's classic text on analysis, the Dover edition of which is under $12 on Amazon [0], has a good (albeit austere) introduction to topology, leading up to it via axiomatic set theory and metric spaces in the book's first chapters. On the one hand, I hesitate to recommend this book, because it was the text for a course that mercilessly exposed the shortcomings in my mathematical education to that time; on the other hand, I recommend it for precisely that reason. Having later assimilated the material, I do consider the book a very good introduction for anyone who either already has the mathematical maturity to do the book properly or for anyone who wants to gain that ability in the way that everybody who has done does: by staring at the same page for hours on end while working everything out on paper, down to the axioms if necessary, until you stop misunderstanding, and then start understanding.

That said, there surely are gentler introductions to the subject if you just want to get a rough idea of it.

[0] https://www.amazon.com/Introductory-Analysis-Dover-Books-Mat...

pash··on Formality – An efficient programming language and proof assistant
I was trying to avoid being too detailed, but the distinction is actually that linear types require function arguments to be used exactly once and affine types require that they be used at most once. So affine types allow constant functions, but linear types don’t. A good place to start for anyone interested in learning more is the Wikipedia article on substructural types [0].

And, yes, you’re right that these type systems effectively implement reference counting at the type level. In practice, linear and affine types are used alongside more general types to permit controlled copying and destruction, which tends to look like manual (but type-enforced) memory allocation and deallocation around the edges.

0. https://en.wikipedia.org/wiki/Substructural_type_system

pash··on Formality – An efficient programming language and proof assistant
Linear logic and affine logic (the latter of which SrPeixinho refers to in that Reddit post) let you use an assumption only once in a proof. Their counterparts in functional programming are called linear and affine types [0]; the arguments of functions with such types are restricted to being used only once in the function’s body. This constraint lets you do some interesting things in compiling and optimizing languages built around these types, and in particular it makes garbage collection trivial.

Linear and affine types are pretty hot right now in the small world of type theory and functional programming. SrPeixinho’s work with his collaborators is aimed at building a language for the Ethereum VM that might actually make it possible to write smart contracts that don’t blow up in your face. It’s good stuff. Search his posts on Reddit to see what he’s up to [1].

0. https://en.wikipedia.org/wiki/Curry–Howard_correspondence

1. https://www.reddit.com/user/SrPeixinho

pash··on Why I never finish my Haskell programs
I think many beginning Haskellers have this problem. To overcome it, my advice is to write Haskell code with the knowledge that you can re-write it more readily than you can re-write code in many other languages. Write the code that fits the immediate application, and rely on the type-checker to make it straightforward to refactor when the need arises.

I think that’s what many experienced Haskellers would say is the language’s best attribute for getting things done, that the type system makes it possible to refactor even a large program with the confidence that all the parts you replace will slot perfectly back into the original structure. Or that changing the core structure itself will result in a new structure that has all the right slots for all the various bits and pieces that need to slot into it. Having the confidence that you will be able to refactor painlessly, you should be less concerned with finding the perfect abstraction up front. Write code, make it work, then make it better.

And as others have mentioned, yes, the right abstraction and appropriate level of generality will become easier to recognize as you write more Haskell. Go with the first decent implementation you can come up with, and as you gain experience that first implementation will more and more often turn out to be a good one. In the meantime, run HLint and read more Haskell code, and you’ll quickly pick up most of the generalizations that really make sense to use in typical applications. The more experienced you get, the more confident you should become that significant time spent generalizing code to no real purpose is pointless and tends to result in code that both reads worse and runs worse than what you started with.

pash··on The Best Textbooks on Every Subject
I’m a big fan of reading textbooks. I tend to buy and read several texts on the subjects that interest me most, and then continually to revisit each of them as my experience and knowledge in the subject broadens and deepens.

But I feel like this sort of list is basically misguided, because the textbook that best suits a reader depends crucially on (a) the reader’s particular background and (b) the reader’s goals in learning a subject. Every textbook on a particular subject is written for a different target audience and emphasizes different aspects of the subject, so in addition to trying to identify overall quality of exposition, prospective readers should try to identify the text that best suits their knowledge and interests as they sit down to read. And after reading one text, a reader’s knowledge and interest in the subject should have changed substantially: his or her interest may be exhausted, but if it’s piqued the reader should then move on to another text that covers the subject more deeply or from a different perspective.

In short, there is no such thing as a “best” textbook. There are good and bad texts, but they’re good and bad for different readers. Well, there are some texts that are just bad and will be bad for just about any reader, but the good ones are all good only for a certain subset of readers whose background in the subject and its prerequisites, and whose goals in learning it, best match what the author had in mind (or implicitly assumes).

pash··on SF hospital charged $15K ‘trauma response fee’ for baby that needed no treatment
John Cochrane, a well known financial economist and former president of the American Finance Association, last month wrote a blog post [0] reacting to a similar article in Bloomberg about the pricing of air ambulance services. If you want to see how bizarre the structure of our markets for healthcare services looks to an economist, I encourage you to read it.

I wonder if there’s a collection of this sort of article somewhere, all these journalistic accounts of ordinary people’s financially nightmarish encounters with the American market for healthcare. It feels like I’ve read dozens of them, and they’re all basically similar, not just in the facts they relate of each debacle, but also in their lack of insight into what’s really so fundamentally broken about our healthcare markets.

0. https://johnhcochrane.blogspot.com/2018/06/cross-subsidies.h...

pash··on Thomas Bayes and the crisis in science
And in fact a Bayesian approach, by being explicit about conditioning information, helps to show the “trick” behind the Monty Hall problem: when Hall opens a door, he reveals information about what’s behind the other two doors that the contestant didn’t have when he made his initial choice. The probabilities change in response to this new information.
pash··on Thomas Bayes and the crisis in science
He’s likely referring to the fact that the rules of probabilistic reasoning can be shown to be the only rules of reasoning that yield correct inferences from data. Bayesian statistics is in that sense the “logic of science”. The first chapter of E.T. Jaynes’s book with that subtitle [0] is a good introduction to these ideas if you haven’t seen them before.

0. E.T. Jaynes (2003), “Probability Theory: the Logic of Science,” http://bayes.wustl.edu/etj/prob/book.pdf [PDF]

pash··on Evidence that drinking baking soda can promote an anti-inflammatory environment
Here’s the Sci-Hub link: http://doi.org.https.sci-hub.hk/10.4049/jimmunol.1701605 [PDF]

Human subjects were dosed 2g (about a fifth of a teaspoon) in 250mL of water each day.

pash··on Einstein's boyhood proof of the Pythagorean theorem (2015)
Einstein’s 1949 article in the Saturday Review is “Notes for an Autobiography” [0]. It’s worth reading.

0. https://archive.org/details/EinsteinAutobiography

pash··on Some Notes About How I Write Haskell
Yes, it’s from the preface to the first edition.

Incidentally, the earliest expression of this idea that I’ve seen is from a talk by Fischer Black [0] in 1963, published a year later in a volume on LISP [1]:

Programming style is not a matter of efficiency in a program. It is a matter of how easy it is to write or read a program, how easy it is to explain the program to someone else, how easy it is to figure out what the program does a year after you've written it; and above all, style is a matter of taste, of aesthetics, of what you think looks nice, of what you think is elegant.

Although style is mainly a matter of taste, a programmer with a "good" style will find his programs easy to write, easy to read, and easy to explain to others. ...

In particular, you may have acquired special programming tricks that you are very fond of, and that aren't used by other programmers, but that don't make your programs much more efficient. I urge you to stop using those tricks. As Samuel Johnson once said, "Read over your compositions, and when you meet with a passage which you think is particularly fine, strike it out."

In other words, make your style simple, not complicated, even though the complicated style may seem to have some abstract virtues. ...

0. Yes, this is the same Fischer Black of the Black-Scholes duo of financial fame. His PhD, informally supervised by Marvin Minsky, was on artificial intelligence. Myron Scholes, for that matter, was also a good programmer and made money programming for economics professors at Chicago while he did his PhD there.

1. F. Black, “Styles of Programming in LISP,” in The Programming Language LISP: Its Operations and Applications, ed. E. Berkeley and D. Bobrow (1964), p96 (p106 of the PDF): http://www.softwarepreservation.com/projects/LISP/book/III_L... [PDF]

pash··on LuLu: An open-source macOS firewall that blocks unknown outgoing connections
The usual convention is a single hyphen for short-form (single-letter) options, and a double hyphen for long-form options:

    > python -v
or

    > python —-version
It’s good practice to offer both. It should also be possible to set multiple options at once by appending one after another in short form following a single hyphen:

    > ls -alR
is the same as

    > ls -a -l -R
Long-form options are technically a GNU thing [0] and are not mentioned in the POSIX standard, but they’re conventional enough now that I think it’s good practice to include them in any CLI program.

There are also a number of looser conventions about the meaning of certain short-form options [1].

0. https://www.gnu.org/prep/standards/html_node/Command_002dLin...

1. http://www.catb.org/esr/writings/taoup/html/ch10s05.html

pash··on AirBnB units drop by 74% due to SF regulations
To expand on that: “Rent” is a term of art in economics that means a “payment to an owner or factor of production in excess of the costs needed to bring that factor into production” [0].

Economic theory shows that in a perfectly competitive market the price of a good equals its marginal cost of production. So prices above marginal cost demonstrate either a lack of competition in the market or other deviations from the theoretic ideal that give producers what economists call “market power”, the ability to charge higher prices for a good than they should be able to charge in a market in which many producers compete to sell more or less indistinguishable items.

Financing costs and all other costs are included in this calculus, so economic “rents” (as a term of art) in the context of the rent charged on homes and other real-estate means something like “excess profits due to a dysfunctional market”; in this case the dysfunctionality of the market is largely the result of regulation that prevents local supply of housing to rise to the level of local demand.

0. https://en.wikipedia.org/wiki/Economic_rent

pash··on Regarding the Em Dash
I do it too, when I’m being lazy. It simply requires more effort to order one’s thoughts well.

The best reference on style I know in this regard is Joseph Williams’s book Style: Toward Clarity and Grace [0]. The book explains how to analyze your own writing to lessen the mental burden on the reader, mainly by re-writing your sentences so that there is a natural logical flow from subject to predicate to object, with detail added in phrases that don’t get in the way.

0. https://sites.duke.edu/niou/files/2014/07/WilliamsJosephM199... [PDF]

pash··on Regarding the Em Dash
The em-dash is like the AK-47: it feels good in one’s own hand, but one is distressed to find it everywhere one looks. If you find yourself wielding either often, you should stop and ask yourself: “Am I the bad guy?”

Just minutes ago I read two articles demonstrating the horror of a world awash in em-dashes, both in The New York Times [0, 1]. One may empathize with the writers, if one is so inclined: they have employed em-dashes for emphasis, to insert asides, and to lend needed structure to their sentences. But I think one should not be so sympathetic, because they’ve used 19 of the damn things (!), and every usage would arguably be improved by substituting another form of punctuation or by restructuring the sentence in a way that eliminates the need for complex punctuation entirely.

The ugliest em-dash is in the second sentence of the first article:

> A new class of security vulnerability — a variety of flaws that affect almost all major microprocessor chips, and that could enable hackers to steal information from personal computers as well as cloud computing services — was announced on Wednesday.

This is an abomination. The writer has needlessly separated the sentence’s subject and predicate by two em-dashes and 28 words in two phrases, burdening the reader with the task of untangling her mess. Did neither she nor her editor care enough about the reader to re-write the sentence trivially in a natural way? Try this:

A new class of security vulnerability was announced on Wednesday, a variety of flaws that affect almost all major microprocessor chips. The flaws could enable hackers to steal information from personal computers as well as cloud computing services.

This use of a double em-dash to insert additional information mid-sentence is almost always the wrong thing to do. Here’s another example from the second article:

> Over the next few years, hundreds of millions of dollars in American deposits flowed from Swiss banking stalwarts — institutions like Credit Suisse and Julius Baer — to Bank Frey.

I propose instead:

Over the next few years, hundreds of millions of dollars in American deposits flowed to Bank Frey from Swiss banking stalwarts like Credit Suisse and Julius Baer.

If you find yourself using em-dashes like this, pause and ask yourself why you can’t render the sentence more naturally. Most times you can, whether by restructuring the sentence, by using standard appositive phrases set off by commas, or by true parentheticals (preferably at the end of the sentence, not dividing the subject and predicate). If you can’t make that work, consider separating the information you wish to convey into two or more sentences.

Here are some more examples of what not to do. From the second article:

> And since the problem is built into the hardware — billions of chips that cannot easily be replaced — fixing this class of problems may also be prohibitively expensive.

Just replace “hardware” with the more detailed phrase and a comma: “... since the problem is built into billions of chips that cannot easily be replaced, fixing ...”

From the second article:

> She would return to the United States secretly carrying just under $10,000 in cash — the cutoff for having to make a customs declaration.

Just use a fucking comma!

Now, if you’ll give me a moment to collect myself in the face of all of this grammatical turpitude, I will say that there are two usages of the em-dash in these articles that I do think sensible. Both set off information in ways that other forms of punctuation can’t (except for the venerable parentheses), and they do so in ways that don’t interrupt the logical flow of the sentence:

> A common trick involves having the microprocessor predict what the program is about to do and start doing it before it has been asked to do it — say, fetching data from memory.

> Prosecutors said all the secrecy — the nameless debit cards, the scissored bank paperwork, the shadowy phone calls — showed Mr. Buck knew what he was doing was wrong.

TLDR: if you use em-dashes often, you might be a lazy writer with a bad editor.

———

0. “The looming digital meltdown,” https://www.nytimes.com/2018/01/06/opinion/looming-digital-m...

1. “A Swiss banker helped Americans dodge taxes. Was it a crime?”, https://www.nytimes.com/2018/01/06/business/stefan-buck-tax-...

pash··on Bitcoin Climbs as Futures Debut Fails to Incite Attack by Shorts
I and some others explained this in another thread [0] about a week ago. The basic explanation is that because of a simple arbitrage relationship between futures and spot, prices in these markets are tightly linked regardless of how the futures contracts are settled.

0. Read the replies to this comment: https://news.ycombinator.com/item?id=15895477

pash··on Bitcoin Futures Start with a Bang as Rally Trips Circuit Breaker
More precisely, it is possible to replicate the final value of a futures contract (on Bitcoin or any other asset) up front, by trading in the spot market, even though a futures contract’s payoff is uncertain until it expires. Whatever the future’s value ends up being at its expiry, you can put together in advance a portfolio of holdings that will have the same value simply by borrowing a certain amount of cash and using it to buy in the spot market a corresponding amount of the asset on which the futures contract is written; if you do this, the value of your holdings in cash (after paying interest on your borrowings) and in the asset are guaranteed exactly to equal the value of the futures contract at expiry, no matter what price the underlying asset ends up trading at then. So if there is any deviation in the value of the futures contract (at any point in its lifetime) from the aggregate value of the cash and assets in the portfolio that replicates its final value, then there is an opportunity for a pure arbitrage. Consequently trading by arbitrageurs bounds futures prices in a tight range determined by the variables that set the cost of putting together this replicating portfolio: the price of the underlying asset, the interest rate on cash and the yield on the asset (if any), the time until the maturity of the futures contract, and cost of transacting in these markets.

This arbitrage relationship is about as hard they get, so trading futures is tantamount to trading the underlying asset itself, since changes in price in the futures market will be translated directly via arbitrage into changes in price in the spot market for the underlying asset, and vice versa.

pash··on The end of the housing supply debate (maybe)
Induced demand [0], if that’s the phenomenon you have in mind, does not mean that “increasing highway capacity increases congestion.” It just means that adding capacity increases usage of the road, often to the point that so many more drivers show up to use the expanded roadway that the improvements do nothing to reduce traffic delays.

There is no economic mystery in induced demand: it’s Economics 101 once you realize that drivers pay for their usage of roads in time, not money. So when a roadway is expanded, all else equal, the cost of driving on it falls—you’re no longer stuck in traffic; but the lower price (that is, travel time) increases demand for use of the road, just as low prices tend to increase demand in other markets. The result is that many more drivers use the expanded roadway, to the point that they bid the price, paid in time waiting in traffic, back up to previous equilibrium level.

(That said, there are ways in which building more roadways can increase congestion itself. Since land use is closely tied to access, building new highways can spur development in far-off areas, causing people to drive more than they otherwise would. There’s also a theoretical possibility that adding new roads can change the roadway topology in ways that cause people to change their routes in ways that create congestion.)

0. https://en.wikipedia.org/wiki/Induced_demand

pash··on The Pricing of Options and Corporate Liabilities (1973) [pdf]
The Black–Scholes–Merton model does assume a log-normal distribution of price changes, and the tails of that distribution are not fat enough to account for the frequency of large price changes observed in real-world markets.

But your criticism is essentially off base. The main reason the Black–Scholes–Merton model remains the workhorse of derivatives pricing nearly a half century on, and the reason two of its creators were given a Nobel prize in 1997, is that the model has proved to be enormously adaptable. One can relax the assumption of constant volatility in various ways, assuming instead that volatilty depends on the price level, on other factors, or that it is itself random. These embellishments retain the Brownian motion and its normal distribution as the primary source of randomness, but the added volatilty structure allows for almost arbitrarily fat tails and all sorts of complicated dependencies in the resulting distribution of price changes.

The fields of mathematical finance and financial engineering are in large part concerned with coming up with tweaks to the Black–Scholes–Merton model that provide the complications necessary to price idiosyncratic securities while maintaining as much of the simplicity of the basic model as possible so that pricing (usually numerically) remains tractable.

As JumpCrissCross pointed out, there have also been numerous follow-on models developed that make different assumptions about the basic distribution of price changes, going back to Merton’s jump-diffusion model of 1980. Most of these models can still be viewed as embellishments of the Black–Scholes–Merton model.

pash··on Blum: “The proof is wrong. I shall elaborate precisely what the mistake is.”
The idea that the domain of science is restricted to falsifiable theories, and is therefore fundamentally empirical, dates only to the early part of the twentieth century. Since the Enlightenment, and also in the much older Western classical tradition, the term science (and its closest translations in Greek, Latin, German, French, and many other languages) has referred much more broadly than that restriction permits, to all fields of knowledge established in a rigorous manner, whether deductive or inductive.

It's in that sense that Gauss crowned mathematics the "Königin der Wissenschaften," the Queen of the Sciences. And indeed in German the term Wissenschaft in ordinary usage still includes mathematics, referring to all knowledge amenable to investigation (as opposed to received knoweldge) [0]. The terms for science in many other Western languages also retain this broader meaning to a greater extent that does contemporary English, and the same is true in many non-Western cultures as well.

The problem here is mainly a terminological one: in English we've found it useful to have a word that refers specifically to the Popperian notion of what counts as science (mainly, I think, to gain the power easily to distinguish "scientific" ideas from "non-scientific" bunk), but we haven't come up with a new term for the older, broader meaning of science as rigorously establishable knoweldge.

I should also point out that Popperian science involves plenty of deductive reasoning—we call it theory—so while it is true that Popper's notion of science requires empiricism, it is not correct to identify it with the distinction between empirical and deductive reasoning. At the same time, the practice of mathematics certainly does involve empirical reasoning, often resulting in a conjecture whose truth is subsequently subjected to rigorous deductive arguments.

(There is a section in the English Wikipedia article on mathematics that discusses this a bit more [1].)

0. https://en.wikipedia.org/wiki/Wissenschaft

1. https://en.wikipedia.org/wiki/Mathematics#Mathematics_as_sci...

pash··on Bitcoin's Academic Pedigree
> "Satoshi" (or this group of people) must have worked months or a year on this before putting it up on source control.

In one [0] of his emails to Mike Hearn [1] Satoshi Nakomoto wrote that he worked on Bitcoin for two years before releasing the paper and code:

> I must admit, this project was 2 years of development before release, and I could only spend so much time on each of the many issues.

His emails to Hearn and others make clear that his creative process consisted mainly of writing code until he was convinced things worked. In my opinion, Satoshi Nakomoto was a lone hacker.

0. https://pastebin.com/wA9Jn100

1. https://bitcointalk.org/index.php?topic=2080206.0

pash··on A quick reminder why Bitcoin was created in the first place
There is no well defined financial distinction between insolvency and whatever you want to call the situation in which the marked to market net value of a bank's assets goes negative due to a fall in prices during a liquidity crisis.† There almost certainly were such situations during the last crisis, when a bank's book value went negative, and yet it was not deemed to be insolvent.

That's because in practice insolvency is not so much a financial concept but an accounting and legal one, and in those domains it refers only to situations in which a corporation cannot meet its financial obligations as they come due. In ordinary circumstances that convention gives corporations some leeway to re-negotiate their obligations to stave off insolvency. But during a liquidity crisis it means that an institution whose book value goes negative (temporarily?—who knows?) will or won't become insolvent in part depending on whether third parties are willing to lend to it to plug the hole that exists in its books at the moment. That means that solvency during such periods is a bit of an artificial thing, depending in part on the of vagaries of the marketplace, as well as the judgement and munificence (or whim, if you'd like) of central bankers and other governmental actors.

> Without fractional reserve banking, there cannot be credit.

This is not true. There can be credit, just not with the simultaneous fiction that creditors retain access to the money they've lent. Bond markets and old-fashioned money-market bank accounts operate without that fiction, for instance.

† — Or for that matter during a classic bank run, which is another form of liquidity crisis. A typical bank operating on fractional reserve is solvent in the sense that over some indefinite future time horizon it should be able to give its depositors their money if they demand it, since the money the bank is owned in loans exceeds the money the bank owes its depositors. But a bank does not enough money in its vaults to pay all its depositors if they all want it back at the same moment; if no third party is willing to lend cash to the bank suffering the run ("provide it liquidity"), then it will become insolvent, no matter what its book value.

pash··on Generating Random Numbers from a Specific Distribution by Inverting the CDF
Statisticians call this inverse transform sampling [0]. The dual result, that Y = F(X) is uniformly distributed for F the cdf of any random variable X, is called the probability integral transform [1].

0. https://en.wikipedia.org/wiki/Inverse_transform_sampling

1. https://en.wikipedia.org/wiki/Probability_integral_transform

pash··on Coffee from California
I don't suppose California's farmers are stupid, so I presume it's someone else's stupidity that has made it attractive to grow coffee, the latest in a long line of water-intensive crops, in dry southern California.

When are Californians going to realize that it's this sort of thing, not a decent shower, that is the cause of the ill effects of a decade of drought? And why do Californians keep subsidizing farmers' water-usage when that is plainly the root of the problem?

pash··on Maine Is Drowning in Lobsters
Quite right!
pash··on Maine Is Drowning in Lobsters
> There is a single party, and it is The State of Maine.

That's an interesting way of looking at it, but it doesn't strike me as one that contributes much to understanding the phenomenon. Individual licensed lobstermen, not the State of Maine, bear the costs and reap the rewards of their catch. The role of the State of Maine is to set rules about how and how much they catch (to their collective benefit), but the state is not in any meaningful sense catching lobsters.

> I fail to see your reasoning here. A single corporate entity would would prefer to employ the smallest number of people possible.

I'm not sure what reasoning you think you're failing to see. I did not say anything about how many people unitary ownership would employ, nor did I express any opinion about the merits and demerits of unitary ownership as a solution to the tragedy of the commons; I only noted that it is one, to illustrate my point that Kelly's characterization of the problem and its solution in terms of "fairness for the many" versus "maximizing for the few" exhibits no understanding of either the problem or the solution and seems to express nothing beyond her sympathies.

pash··on Maine Is Drowning in Lobsters
> Kelly argues that this ownership of the lobstering commons, in a cooperative-like structure, leads to greater sustainability.

>> Large corporate boats can operate only in designated areas. Instead of permitting limitless liberty to absentee owners for the seeking of wealth -- by hired hands indifferent to local custom -- Maine set spinning a new governing pattern…. That the right to make a living comes before the right to make a killing. That fairness for the many is more important than maximizing for the few. That sustaining the prosperity of larger living systems, both human and wild, is the root condition for the flourishing of all.

At least insofar as Kelly's argument pertains to the management of fisheries and other commons, it is—economically speaking—more wrong than right.

A tragedy of the commons can be avoided in several ways, and none of them has much to do with putting "fairness for the many" ahead of "maximizing for the few". Indeed, a tragedy of the commons arises only when "the many" have unrestricted access to a scarce resource, and proceed to exploit it in an unsustainable way, due to the strategic nature of the situation.

Kelly would have you think otherwise, but "large corporate boats" are not the root cause of overfishing; the root cause is the desire on the part of each fisherman in an unregulated commoms to haul in the biggest catch he can before someone beats him to it. So aside from imposing regulation, another way to prevent a tragedy of the commons is to get rid of the commons: grant exclusive use of the former commons to a single party, who then has an incentive for good stewardship.

And quite contrary to Kelly's characterization of it, Maine's solution to managing its lobster rights can be seen as an instance of favoring the few over the many: lobstering was restricted to a relative few legally priveledged parties, few enough to make coordinating sustainable lobstering practices feasible. As is often the case when the law arbitrarily privileges some parties over others, there is an overlooked harm here, suffered by would-be lobstermen that the rules say cannot be.

So it seems to me that Kelly's words express her worldview and her somewhat misplaced good intentions—it is the curse of the economically uninformed that their good intentions will often lead them to a destination they didn't seek—but nothing more.

pash··on For First Time Since 1800s, Britain Goes a Day Without Burning Coal for Power
This is an astoundingly vapid article. If you want to understand why and how the UK has so quickly reduced the amount of coal it burns, Carbon Brief has a much more informative overview [0].

The basic explanation of what happened is simple: the UK instituted a carbon tax that made coal more expensive than natural gas per unit of electricity produced, so British utilities shut down their coal plants and replaced them with gas plants as quickly as possible.

The backstory is somewhat more complicated, and much more interesting. The British tax was implemented in 2013 as a local fix to a broken EU carbon-trading program; that program, called the Emissions Trading Scheme [1], allocated to electrical utilities in the EU the right to produce a fixed amount of carbon emissions (and carbon-equivalent emissions), and the rights were made transferable—a typical cap-and-trade set-up. And then the basic problem with that typical set-up occurred: the fixed supply of rights to produce emissions proved higher than the EU's electrical sector's total demand, a consequence mostly of lower than expected demand for electricity during the recession that followed the financial crisis of a decade ago, but also partly due to other clean-energy initiatives and to big changes in world energy markets. And so the price of emissions rights collapsed.

That wasn't really a problem—no more carbon was being pumped into the air than the ETS allowed—but it made plain the fact that the ETS was doing nothing at all to reduce emissions. So British lawmakers decided to implement their own carbon tax, called the Carbon Price Floor [2], in order to reduce emissions and support the development of clean energy. The tax rate Parliament set was one of the highest in the world, and as it turned out it was just high enough to make coal slightly more expensive than natural gas for generating electricity, an outcome entirely unforeseen when the policy was decided, just as global production of natural gas was beginning to boom and its price to plummet.

So in the end, a bunch of poorly designed policies and their unforeseen consequences led to a better than expected outcome: Britain has been weened off coal decades earlier than was thought possible.

0. http://www.carbonbrief.org/analysis-uk-cuts-carbon-record-co...

1. https://en.m.wikipedia.org/wiki/European_Union_Emission_Trad...

2. https://www.gov.uk/government/publications/carbon-price-floo...

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