Bitcoin and the bubble theory of money

A few months ago Vijay Boyapati asked me to "steel-man" the bubble theory of money. The bubble theory of money, which can originally be found in a few old Moldbug posts, has been used by Vijay and others to explain the emergence of bitcoin and make predictions about its future.

So here is my attempt. I am using not only an article by Vijay as my source text, but also one by Koen Swinkels, a regular commenter on this blog. Both are interesting and smart posts, it's worth checking them out if you have the time.

Steel-manning the bubble theory of money and bitcoin

1. Unlike a stock or a bond, which is backed by productive assets, bitcoin cannot be valued using standard discounted cash flow analysis. And since it has no intrinsic uses, it can't be valued for its contribution to various manufacturing processes, nor for its consumption value. Rather, bitcoin is a bubble. Its price is driven by a speculative process whereby people buy bitcoins because they think that other people can be found who will pay an even higher price.

2. There is no reason why bitcoin must pop. At first, bitcoin will be bought by those on the fringe. As more people get in, the price of bitcoin will rise further. It will continue to be incredibly volatile along the way. But once bitcoin is widely held (and very valuable), the flow rate of incoming buyers will fall, and so will its volatility. At this point it has become a stable low-risk store of value. The eventual stabilization of bitcoin's price is a commonly held view among the bitcoin cognoscenti. For instance, bitcoin encyclopedia Andreas Antonopoulos has often said the same thing (i.e. "volatility really is an expression of size").

3. Once its price has stabilized, bitcoin can transition into being a widely used money, since people prefer stable money, not volatile money.

So having steel-manned the bubble theory of money as applied to bitcoin, where do I stand?

I agree with points 1 and 3. My beef is with the middle point.

Will a Keynesian beauty contest ever stabilize?

First off, let me point out that there are elements of the second argument that I agree with. Yes, bitcoin needn't pop, although my reasons for believing so are probably different from Koen and Vijay.  In the past, I used to think that a popping of the bitcoin bubble was inevitable. After all, as a faithful Warren Buffett disciple, I believed that the price of any asset eventually returns to its fundamental value, and bitcoin's is 0.

But the eternal popularity of zero-sum financial games, or gambles, has disabused me of this view. People are lured by the promise of winning big and changing their lives without having to do any work. Heck, even though a Las Vegas slot machine will take on average 8 cents from every $1 wager, people still flock to insert $1 bills into slots. And so they will play bitcoin too, which like a slot machine is also a zero-sum game.

But I digress. The key point I want to push back on is Vijay and Koen's assumption that bitcoin volatility will inevitably decline as it gets more mature. I'm going to accuse them of making a logical leap here.

If bitcoin is fundamentally a bubble, or—as Vijay describes it—if bitcoin's price is determined game-theoretically, then why would its price dynamics change if more people are playing? Almost a century ago, John Maynard Keynes described this sort of game as a beauty contest. Presented with a row of faces, a competitor has to choose the prettiest face as estimated by all other participants in the contest:

"...each competitor has to pick, not those faces which he himself finds prettiest, but those which he thinks likeliest to catch the fancy of the other competitors, all of whom are looking at the problem from the same point of view. It is not a case of choosing those which, to the best of one’s judgment, are really the prettiest, nor even those which average opinion genuinely thinks the prettiest. We have reached the third degree where we devote our intelligences to anticipating what average opinion expects the average opinion to be. And there are some, I believe, who practise the fourth, fifth and higher degrees."

Whether 100 people are participating in Keynes's beauty contest, or 10,000, the nature of the game has not changed—it is still an nth degree mind-game with no single solution. Since the game's underlying nature remains constant as the number of participants grows, its pricing dynamics—in particular its volatility—should not be affected.

The stabilization of Amazon

We can think about this differently by using actual examples. I know of an asset that has become less volatile as it has gotten bigger: Amazon. See a chart below of its share price and volatility over time:

Why has Amazon stabilized, and will bitcoin do the same? When Amazon shares debuted back in 1997, earnings were non-existent. Jeff Bezos had little more than a hazy business plan. Since then the stock price has steadily moved higher while median volatility has declined. Amazon shareholders used to experience day-to-day price changes on the order of 2.5-4.5% in the early 2000s. By the early 2010s, this had fallen to 1-2% or so. Over the past several years, volatility has typically registered between 0.5-1%.

I'd argue that the stabilization of Amazon hasn't been driven by a larger market cap and/or growing trading volumes. Under the hood, something fundamental has changed. The company's business has matured and earnings have become much more stable and predictable. And so has its stock price, which is just a reflection of these fundamentals.

I've just told a reasonable story about why a particular asset has become less volatile over time. But it involves earnings and fundamentals, two things that bitcoin doesn't have. I'm not aware why a Keynesian beauty contest, which lacks these features, necessarily gets less volatile as more people join the guessing game.

Vijay and Koen draw an analogy between gold and bitcoin. Their claim is that if gold once transitioned from being a volatile collectible into a low-risk store of value, then so can bitcoin. But we really don't have a good dataset for the price of the yellow metal, so we really have no idea how its volatility changed over time. Going back to 1969—admittedly far too short a time-frame—gold has certainly increased in size (i.e. the total market value of above-ground gold has increased), but unlike Amazon there is no evidence of a general decline in price volatility:

I'd argue that in gold's case a lack of a correlation between size and volatility makes sense. A large portion of gold's daily price changes can be explained by speculators engaging in a Keynesian beauty contest, not changes in industrial demand or earnings (unlike Amazon shares, gold doesn't generate income). There's no good reason to expect that the volatility generated by gold speculators' beliefs should level off as participation in the "gold game" grows. Any game in which speculators base their bets on what they expect tomorrow's speculator to do, who in turn are guessing about potential bets made by next week's speculators, who in turn form expectations about the choices made by next month's players, is unlikely to converge to a stable answer for very long.

Will Proof of Weak Hands 3D tokens ever become money?

As a third example, let's take Proof of Weak Hands 3D (PoWH3D), an Ethereum dapp that I've blogged about a few times. PoWH3D is a self-proclaimed ponzi game. Basically, a player purchases game tokens, or P3D tokens, with ether. Each player's ether contribution goes into the pot, or the PoWH3D smart contract, less a 10% entrance fee which is distributed pro-rata to all existing P3D token holders. When a player wants to exit the game, their tokens are sold for an appropriate amount of ether held in the pot, less another 10% that is distributed to all remaining players.

So if a new player spends one ether (ETH) on some P3D tokens only to sell those tokens an instant later, they'll end up with just 0.81 ETH, the first 0.1 ETH having been paid to everyone else upon the new player's entrance, the other 0.09 being deducted upon their exit. Why would a new player take such a bad bet? Only if they believe that a sufficient number of latecomers will join the game such that they'll get enough entrance and exit income to compensate them for the 0.19 ETH they have already given up.

PoWH3D is a pure Keynesian beauty contest. A new entrant's expectations are a function of whether they believe latecomers will join, but latecomers' expectations are in turn a function of whether they believe yet another wave of even greater fools will pile in, etc, etc.

Applying Koen and Vijay's assumption that volatility decreases with adoption, then the return on P3D tokens should become less volatile as more people join. It might even transition into a stable investment, say like a blue chip utility stock. Who knows, it could even become a medium of exchange to rival the dollar. But surely Koen and Vijay don't want to walk out on a limb and argue that a pure ponzi game like PoWH3D will ever stabilize. Or that it might become a form of money. I think the most reasonable thing we can say about PoWH3D is that once a ponzi game, always a ponzi game. The volatility of its returns will not decline as the game grows, and that's because the game's fundamentals, its ponzi nature, doesn't vary with size. (If you are interested in PoWH3D, here are some great charts and stats).

At this point, it may be useful to map out a chart of bitcoin's 200-day median volatility. As in the case of Amazon and gold, I use the median rather than the average to screen for outliers:

new Bitcoin volatility chart from @jp_koning

based on the 200-day rolling median daily price change: pic.twitter.com/U3zfHPQsVd

— Tim Swanson (@ofnumbers) August 20, 2018

I haven't updated the chart for two months, but volatility has declined since then. Vijay and Koen will probably say that as of October 2018 bitcoin is less volatile than it was in 2011. That's certainly true. But eyeballing the chart, we certainly don't get the same clean relationship between size and volatility as we do with the Amazon chart.

Here's the biggest oddity. By December 2017 bitcoin had reached a market cap of $300 billion, its highest value to date. If Vijay and Koen are right, peak size should have corresponded with trough volatility. But this wasn't the case. In late 2017, bitcoin volatility was actually quite high. In fact, it exceeded levels set in late 2013, back when bitcoin was still a tiny $3 billion pup! The lesson here is that with bitcoin, bigger is just as likely to correspond with more volatility as it is with less volatility. More broadly, when it comes to Keynesian beauty contests there seems to be no fixed relationship between volatility and size. It's chaos all the way down.

This leads into Koen and Vijay's final point, that once bitcoin's price has stabilized, it can transition into a widely used money. I agree with the underlying premise that only stable instruments will become accepted by the public as media of exchange. But since I don't see any reason for bitcoin to stabilize, I don't see how it will make the leap from a speculative instrument to a popular means of paying people.

Bitcoin isn't on the verge of going mainstream. It's already there.

Vijay's message (Koen's not so much) can be taken as investment advice. Because if he is right, and bitcoin has yet to progress to a popular store of value and finally a medium of exchange, then we are still in the first innings of bitcoin's development. Vijay points to what he thinks are the features that will make bitcoin win out against other popular stable assets, including portability, verifiability, and divisibility.  Given that only the “early majority” has adopted bitcoin (the late majority and laggards still being far behind), Vijay thinks it would be reasonable for the price of bitcoin to hit $20,000 to $50,000 on its next cycle, and hints at an eventual price of $380,000, the same market value of all gold ever mined. So buying bitcoin now at $6,000 could provide incredible returns.

I have different views. Whereas Vijay thinks bitcoin has yet to go mainstream, I think that bitcoin went mainstream a long time ago, probably by late 2013. Bitcoin is often portrayed (wrongly) as a payments system-in-the-waiting, and thus gets unfairly compared to Visa and other successful payments systems. Given this setup, cryptocurrencies seems to be perpetually on the cusp of breaking out as a mainstream payments option. But bitcoin's true role has already emerged. Bitcoin is a successful decentralized gambling machine, an incredibly fun censorship-resistant Keynesian beauty contest.

Viewed this way, bitcoin's main competitors were never the credit card networks, Citigroup, Western Union, or Federal Reserve banknotes, but online gambling sites like Poker Stars, sports betting venues like Betfair, bricks & mortar casinos in Vegas, and lotteries like Powerball. By late 2013, bitcoin was at least as popular as some of the most popular casino games, say baccarat or roulette. It had hit the big leagues.

Whereas Vijay hints at a much higher price, where do I see the price of bitcoin going? I haven't a clue. But if I had to give some advice to readers, I suppose it would be this. Like poker or slots, remember that bitcoin is a zero-sum financial game (For more, see my Breaker article here). You wouldn't bet a large part of your wealth in a slot machine, would you? You probably shouldn't bet too much with bitcoin either. Vijay could be right about bitcoin hitting $380,000. It could hit $3.80 too. But if it does go to the moon, it will do so for the same reason that a slot machine pays off big.

It's worth keeping in mind that when it comes to gambling, the house always wins. Searching around for the lowest gambling fees probably makes sense. As I said earlier, Las Vegas slots will extract as much as 8 cents per dollar. Lotteries are even worse.

In bitcoin's case, the "house" is made up of the collection of miners that maintain the bitcoin system. All bitcoin owners must collectively pay these miners 12.5 bitcoins every 10 minutes to keep things up and running. So if you hold one bitcoin and its market value is $6000, you will be paying around 62 cents per day in fees, or $230 per year. That works out to a yearly management expense ratio of 3.8%. Beware, this number doesn't include the commissions that the exchanges charge you for buying and selling.

So before you start gambling, consider first whether the benefits of decentralization are worth 3.8% per year. If not, find a centralized gambling alternative. If the costs of decentralization are worth it, then buy some bitcoin, and good luck! But play responsibly, please.

Arbitraging the 49th parallel

Thanks to a floating exchange rate and one of the longest undefended frontiers in the world, the U.S.-Canada border is the thoroughfare for what may be one of the world's most popular ongoing consumer arbitrages.

Canada and the U.S. interlist all sorts of goods, services and financial assets. We both sell McDonald's hamburgers, we both offer tickets to NHL games, and we both list Valeant Pharmaceutical shares. The relative price of Valeant shares, which trade in New York and Toronto, will rapidly adjust to any change in the exchange rate. If not, then upon an appreciation of the U.S. dollar an investor will be able sell Valeant short in New York at an artificially high price, buy Canadian dollars with the proceeds, and acquire shares in Toronto on the cheap, using those shares to cover the short position in New York at a profit. Exploitation of this opportunity will realign Valeant's New York and Toronto share price until the window closes, thus cannibalizing the potential for arbitrage gains. This process takes seconds.

Financial prices are set "immorally." In the moral economy of Main Street, goods and services prices stay fixed for long periods of time. At time = 0, say that Big Macs and hockey tickets have the same real price in the U.S. and Canada so that people have no reason to prefer shopping in one country or the other. The moment that the Canadian dollar appreciates, a consumer arbitrage window opens that allows Canadians a chance to boost their welfare. Since sticker prices in the U.S. don't change, Canadians can now cross the border and buy more Big Macs and hockey tickets than they could if they had stayed parked in Canada. So much for the law of one price. This window will stay open for quite some time. Bils and Klenow (pdf), for instance, report that lunch menu prices in the U.S. only change once every 10.6 months while sporting event admission prices only adjust once every 3.9 months. (That's almost eleven months of free lunches.)

The chart below, which uses data from the Canadian Border Services Agency, illustrates how North American migration patterns fluctuate as the arbitrage window switches in favor of either the U.S. or Canada.

As the chart shows, the difference between Canadians visiting the U.S. and Americans visiting Canada (the green dotted line) is correlated to movements in the exchange rate. A weak loonie in the early 1980s and 1992-2002 encouraged more Americans to visit Canada while decimating the hoards of snowbirds headed south. The strong Canadian dollar from 1986-1992 and 2002-2011 did the opposite, stifling American visits while inspiring Canadian exits. The loonie's plunge over the last twelve months, aggravated by the collapse in crude oil prices, has finally begun to bring increasing amounts of Americans over the border for the first time in over a decade.

Going forward, expect to see more stories like this ("explosive growth" in Alberta ski hill bookings for this winter), this (Montreal sees best tourism season in years), this (Thunder Bay's tourism picks up) and this (bad news for Buffalo's airport).

Or course, you can't get something for nothing forever. Prices are rationing devices. When a good's price is fixed at an artificially low level then costly lineups will develop, substituting for price signals as a rationing device. The sudden undervaluation of goods & services on either side of the 49th parallel as the exchange rate fluctuates should give rise to congestion at the border, modulating the size of the consumer arbitrage window.

By the way, the chart above illustrates one of the advantages of having a floating exchange rate. Without a collapse in the loonie, price ratios between the U.S. and Canada would have remained much more rigid over the last twelve months, preventing the emergence of a consumer arbitrage opportunity in favour of American consumers. Canadian aggregate demand, already depressed by weakness in the energy sector, wouldn't be benefiting from an influx of American shoppers and returning Canadians. Unemployed oil workers in Fort McMurray wouldn't be getting the opportunity to find work on Banff's booming ski hills.

Sweden and peak cash

The Swedes really don't like cash. First, consider that Sweden is the only country in the world that I'm aware of where reliance on paper money is in decline. Second, no country's central bank has produced a nominal deposit rate as negative as Sweden's, for as long. Yet even at -0.85% per year, Swedish banks who own those deposits haven't fled into 0% cash, providing some indication of the degree to which they hold banknotes in disdain.

ABBA won't accept paper

As the chart below shows, cash outstanding continues to grow in almost every country except Sweden. Japan and Denmark are the only countries that come close to pacing the Swedes, although both nations continue to show incremental growth in demand for banknotes. Even Kenya, where m-pesa has taken hold, shows strong cash demand.

Sweden reached "peak-cash" somewhere between 2007 and 2008. The reason for this change of heart is public preferences, not government diktat. The monetary authorities can only indirectly influence the demand for cash, say by introducing/removing various banknote denominations, or altering the quality of its note issue (say by making notes harder to counterfeit). By virtue of deposits being convertible into cash whenever the depositor desires (and vice versa), the allocation between cash and deposits is primarily up to the public, not the monetary authorities.

One theory is that Sweden become more law-abiding in 2008, thus reducing their demand for paper kronor. Cash is typically demanded by criminals and tax evaders to avoid creating a paper trail. That Sweden's underground element suddenly decided to go legit doesn't seem very plausible to me. Demographics is a more likely contributor to peak cash. As a nation's population growth slows, the demand for cash peters off with it. This can't be the entire explanation, however, since other countries that also suffer from poor population growth profiles (like Canada) show rising cash demand. This leaves technology as the most likely culprit. As electronic payment options improve, it makes little sense to endure the hassle of withdrawing and holding a small horde of dirty paper in one's wallet.

According to a MasterCard study, 89% of transactions in Sweden are cashless, compared to 80% in the U.S. Situation Stockholm, the street paper sold by homeless vendors in Sweden's capital, can be purchased with a card rather than cash, and while London's buses went cash-free earlier this year, bus fares disappeared several years ago in Stockholm. Unlike the U.S. and other laggards, Sweden has a near real-time person-to-person payments system called Bankgirot which has been active since 2011. Bank customers can download an app called Swish, which allows them to make immediate mobile payments over the Bankgirot network. In southern Sweden, Vicar Johan Tyrberg has installed a card reader to make it easier for worshipers to make offerings. And finally, despite having a hit song entitled Money, Money, Money, ABBA refuses refuses to accept cash at the ABBA Museum. Apparently ABBA member Bjorn Ulvaeus is leading a crusade against banknotes after his son's apartment was burgled twice.

No zero lower bound, at least not yet

As a second illustration of Swedish cash abhorrence, consider that no other central bank has maintained a negative deposit rate as low as Sweden's central bank, the Riksbank, for as long. The Riksbank reduced its deposit rate to -0.85% this month after having maintained it at -0.75% since October 2014. A few nations come close. The Swiss, for instance, reduced rates to -0.75% in January, as have the Danes—but both are behind the pace set by the Swedes.

The key point here is that with Riksbank deposits being penalized 0.85% per year, one would assume that that they'd be quickly converted into Swedish banknotes. Cash, after all, pays 0% a year, superior to -0.85%. But that hasn't happened. As the chart below shows, cash left on deposit at the Riksbank stands at around 150 million kr, roughly the same level it has been at for the last twelve months (and far above 2008-2012 levels).

Who keeps funds on deposit at the Riksbank? As the business day progresses and Swedes make payments among each other, banks who maintain settlement accounts at the Riksbank will find themselves in a surplus or deficit position. While those in surplus can elect to park their excess at the Riksbank's overnight deposit facility, they'll usually try to lend these positions to deficit banks in the interbank lending market or participate in Riksbank fine-tuning operations at the end of the day, both of which provide superior returns to the deposit rate. For whatever reason, Swedish banks typically leave a small portion of their surplus in the deposit facility, bearing the awful return on deposits for the sake of enjoying whatever conveniences the deposit facility offers.

That this 150 million kr in -0.85% yielding deposits hasn't been converted into cash is an indication of just how low Swedish opinion on cash has sunk. Consider the myriad number of costs a bank that wants to cash out its balance will have to incur. A Brinks truck must be hired in order to transport the cash to the bank's vaults. The cash must be counted, requiring a diversion of tellers' resources from other important activities. With the majority of Swedish bank branches having gone cashless, they may need to reinvest in handling infrastructure before they can take delivery of a truck full of banknotes. Next, that cash needs to be vaulted, which means displacing other valuables from being safeguarded (like a client's jewels), forcing the bank to forfeit a vaulting fee. Finally, the cash needs to be insured from theft. No wonder Swedish banks continue to use the Riksbank's deposit facility, even at a -0.85% rate; like the public, banks don't consider cash to be a convenient option.

Could Swedes one day re-embrace cash?

Swedes are proud of their move towards digital payments, but this trend could very rapidly come to an end. In an effort to hit its inflation target, the Riksbank may have to push interest rates even deeper into negative territory. At much lower levels, even the most cash-hating Swedes will have to re-consider their aversion to paper. The consequences could be significant. While only a small quantity of deposits are kept in the Riksbank's deposit facility, much larger amounts—around 30 billion krone—are invested at the Riksbank via overnight fine-tuning repos, which currently pay -0.2%. If the Riksbank reduced the fine-tuning rate much lower (say to around -1.5%), these repos would be rapidly converted into cash by banks. The public holds many hundreds of billions more worth of deposits at Swedish commercial banks. Should Riksbank rate reductions force banks to respond by ratcheting down their own deposit rates to -1 or -2%, how long before Swedes empty out their bank accounts, turning Sweden into a cash-only economy?

To avoid reverting to a cash-only economy at extreme negative rates, the Riksbank would do well to hitch itself to the cashless trend. One way to go about this without calling in all banknotes would be to reign in the number of paper products the central bank currently offers consumers, in particular high denominations of notes. Just stop allowing conversions into the 1000 krona note, and maybe the 500 krona note too, or consider canceling these large denominations outright. Not only would this reduce the central bank's printing costs, but it would provide more room for further rate cuts into negative territory—without the threat of a mad dash into Swedish cash.

As for the rest of us...

As in Sweden, I'm pretty sure that cash demand in places like Canada and the US will eventually peak as continued advances in payments technology and a more rapid adoption of those technologies lead consumers to demand less of the stuff. Central banks might consider adapting to this trend ahead of time by reducing the number of paper products they offer to the public. Do the Swiss really need a 1000 SFr note? Do Europeans need a €500 note, and Canadians $100 notes? Alternatively, why not do what Bill Woolsey advocates? Let's gradually privatize the issuance of paper currency. If anyone can make cash relevant again, it's innovators in the private sector. And if they can't, then maybe the banknote deserves to die a slow death.

Secondly, Sweden shows that the so-called zero-lower bound isn't actually at zero, but some distance below that. Cash is awfully burdensome, as evidenced by Swedish banks who are willing to hold deposits at -0.85% despite the option to earn 0%. Central bankers at the Federal Reserve, ECB, and elsewhere would do well to heed this Swedish data point. If they need to loosen monetary policy in order to hit their targets, they can go well below -0.5% before having to fear mass conversion into cash. The world's central bankers have much more interest rate ammunition than they let on.

Beware the financial Jeremiahs

Jeremiah, the prophet of impending disaster. By Rembrandt, 1690. See full version.

The 1929 analog model has resurfaced.

The 1929 analog is a recurring visual meme, usually a chart, that periodically plagues financial markets. All versions of this meme invariably map the bobbing and weaving of the 1929 Dow Jones Industrial Average onto movements in the present Dow, with the inevitable conclusion being that we are, by analogy, on the verge of a repeat of the 1929 crash.

The most recent reincarnation originates from noted market timer Tom DeMark. His claim has been amplified by newsletter writer Tom McClellan and irresponsibly blared all over the internet by Marketwatch (see here, here, here). I produce the chart below:

Source: Marketwatch

I've been following various flareups of the 1929 analog for over a decade. They usually crop up in September, just before the anniversary date of the October 29 crash. Extended bull markets are particularly fertile ground for 1929 analog behaviour as the long run-up to the 1929 crash will typically map quite well to the current bull market. Financial Jeremiahs, those whose bread and butter is to perpetually predict hard times, are a major source of these graphics. The meme typically dies a quick death as market movements subsequently fail to conform to the analogy. DeMark's version has received far more press attention than any of the other flareups I've followed, thus this post.

The 1929 analog chart always has been and always will be silly. Worse, there is always a small chance that the chart will have large repercussions (more on that later).

The chart is silly because there's no logic behind it. It simply doesn't follow that the alignment of prices today with prices from eighty years ago means that subsequent prices must adhere to the old path. There's little else to be said.

What makes the chart so effective isn't the logic that underlies it (there is none), it's because it harnesses our brain's automatic ability to rapidly complete patterns. Our brains are always trying to pick out visual regularities in the chaos, or to generalize. This is an incredible power, allowing us to recognize a face at night using only a few cues, or pick out a dalmatian against a camouflaged background (see picture below).

When we look at the 1929-2014 analog, the chart is virtually begging us to complete the pattern. Note, for instance, how the red line has been placed a constant distance below the blue line rather than having the lines cross over each other. This isn't an accident—it's a feature designed to crystallize the comparison in the mind of the viewer. Any crossing over of lines would only impede the viewer's ability to rapidly make the analogy.

In the same way that we get an aha! moment the moment that we finally tease out the dalmatian from its surroundings, the transferral of the 1929 crash onto the as-yet incomplete 2014 plot provides us with a burst of satisfaction. So we stop thinking, the puzzle seemingly complete. The long and sober thought processes that should go into forecasting a major turn like a crash is short-circuited by the superficial sense of completion that the overlay of prices gives us. And that's what the chart maker wants, to short circuit are deeper thought processes by appealing to our innate propensity to rapidly fill in the visual blanks.

Unfortunately, this silly chart has a very small chance of having large repercussions.

Assiduous readers may remember that I wrote about the 1929 analog last October. In that post I hypothesized that the best explanation for the 1987 stock market crash was an emergence of the 1929 analog meme. The mechanism would have worked something like this...

At some point in 1987 stock prices began to randomly overlap with a plot of 1929 prices. Traders found meaning in this fluke and began to trade using the 1929 trajectory as a guide. Paradoxically, their trading helped push prices in the same direction as the 1929 plot, reinforcing the similarity between the two charts. This would have only increased the degree of belief they placed in the analog, causing them to increase their 1929-inspired trading, this activity creating ever more conformity between 1929 and 1987 prices. A feedback loop had been created, a loop that would only have expanded as traders told their friends about the pattern, thus expanding the size of the population who was driving the process. The feedback loop finally culminated in a self-realization of the 1929 crash on Monday, October 19, 1987. (This is just a short summary, go read the full article.)

This is why DeMark's 1929 analog, amplified by the likes of McClellan and Marketwatch, has the potential to be dangerous. Despite being no more than a silly picture, if enough people believe in it, that silly picture could actually inspire a stock market crash. Markets, after all, are reflexive. Fundamentals usually drive the ideas that people use to inform their trading behaviour. But at other times, ideas get a life of their own, and when enough people adopt them, these ideas create the very underlying reality that they only claimed to predict. In markets, silly beliefs can become true.

The way I see it, it's our duty to provide a counterbalance to destabilizing reflexive forces like these by either ignoring financial Jeremiahs or roundly vilifying their ideas. After all, sharp downturns are healthy insofar as they are justified by actual events and changes in the fundamentals, but if they're created by mass faulty thinking, everyone is made worse off.

I couldn't help but notice that DeMark was employed by Tudor Investments from 1988 to 1990. Interestingly, Paul Tudor Jones, founder of Tudor Investments, made a pile of money during the 1987 crash by basing his trades on a 1929 analog model (again, read my old post). It would seem that DeMark isn't doing anything new, he's simply repeating a time tested strategy once used by his former employer. A cynic would say that folks like Tudor Jones and DeMark spread the 1929 analogy not because they actually believe in it, but because they want to harness people's tendency to overgeneralize for their own gain. If enough proles take the hook, then markets could plunge, thus benefiting Tudor Jones's and DeMark's pre-existing trading positions. I'm sure that's not the case and that all parties are being genuine. But advertising a trade after one is already in it, i.e. talking one's book, is a time honoured strategy among finance professionals.

With the Dow having such a good performance in February, the simplistic analogy between 1929 and 2014 is slowly being stretched to the point that it no longer aligns. It looks like the DeMark's analog model could die a natural death. However, there's a simple strategy often used by those calling for the end of times. When Warren Jeffs, president of the Fundamentalist Church of Jesus Christ of Latter-Day Saints, predicted the end of the world on December 23, 2012, and it failed to happen, he changed the date to December 31. The 1929 analog can simply be redrawn, shifting the entire 1929 plot over to give more time for the our current market to ripen towards an imminent crash. Even if DeMark isn't the one to do it, someone else will draw the analogy. The longer the current bull market continues, the more fertile the ground will be for these sorts of destabilizing memes.

---

P.S.: Most commentators have been vilifying the chart, which is good. (See Matthew Boesler, The Reformed Broker, Matthew O'Brien, and the Wall Street Journal). Their criticisms are mostly along the line of... "the analog is less apparent if we rescale the axis." They use something like the chart below as their rebuttal in order to decouple the performance of 1929 and today.

Source: Business Insider

This rebuttal is a weak one since it gives too much ground to the supposed logic that underpins the 1929 analogy. Say that the two plots were to be correctly scaled and say that the prices in one era closely aligned with the other. There would still be no good reason to assume that the current period must follow the prior one into a nosedive. In attacking the scale of the chart, critics are missing the larger error that underpins the 1929 analog.

In short, don't give into your brain's rapid ability to complete these facile patterns. A truly well-reasoned crash prediction would require such a massive allocation of mental power to arrive at that no one would ever actually get there. Admittedly I'm being a nitpicker here. Though the various rebuttals all appealed to the same bad logic that the original chart did, at least they helped counter the reflexive properties of the most recent appearance of the 1929 analog. An enemy of my enemy is my friend, I suppose.

The best way to use stacked area charts to visualize crazy central bank balance sheets

Before 2008, visualizations of central bank activity largely focused on interest rates. These visualizations were easy to make, just a line graph showing a central bank's target rate and the actual overnight rate, perhaps within a narrow channel bounded at the top by the central bank's lending rate and at the bottom by its deposit rate. The one below, pinched from the Economist, is a decent example.

But then the credit crisis hit. Rates plunged to zero where they have stayed ever since. Central bank policy moved away from conventional manipulation of the short term rate towards more unconventional policies, thus rendering the classic line graph less relevant.

Two of the more important of these new unconventional tools are quantitative and qualitative easing. A good chart must be capable of illustrating the expansion of a central bank's balance sheets (quantitative easing) and contortions within that balance sheet (qualitative easing). In this context, stacked area charts have become the go-to visualization. Not only can they convey the overall size of the central bank's balance sheet and its change over time, but they are also capable of showing the varying contributions of individual stacked areas, giving a sense of movement within the balance sheet.

Because the stacked area chart's large flat areas are typically filled with colours, it reigns as one of the charting universe's more visually stunning specimens, appearing almost Van Gogh-like in its intensity. However, there are a few interesting technical problems with using stacked area charts, two of which I'll describe in this post:

1. Small sums get squished

QE has in many cases caused a quadrupling in size of central bank balance sheets. However, pre-QE and post QE periods must share the same scale on a stacked area chart. As a result, pre-QE data tends to get squished into a tiny area at the bottom left of our stacked area chart while post QE data gets assigned to the entire length of the scale. This limits the viewer's ability to make out the various pre-QE components and draw comparisons across time. The chart below, pinched from the Cleveland Fed, illustrates this, the data in 2007 being too squished to properly make out.

The classic way to deal with the squishing of small amounts by large amounts is to use a logarithmic scale. Log scales brings out the detail of the small amounts while reducing the visual dominance of large amounts. The chart below, for instance, illustrates what happens when we graph Apple's share price data on the two different scales.

But log scales don't work with stacked area charts. Below, I've stacked three data series on top of each other and used a logarithmic scale.

Upon a quick visual inspection, you might easily assume that the blue area, Series1, represents the greatest amount of data, the purple the second most, and the yellow the third. But all three represent the same data series: 4, 4, 6, 8, 3, 4. If you look closer and map each series to the logarithmic scale, it becomes evident that all three areas indeed represent the same amount of data. Since the series represented by the blue area happens to be the first series, the log scale assigns it the largest amount of space. If by chance the data represented by the yellow series was first in line, then it would be assigned to the bottom part of the scale and would take up the most area. This is an arbitrary way to go about building a chart.

So applying a log scale to a stacked area chart will cause most people to gather the wrong conclusions. They are interested in the size of the areas, but a log scale assigns equal data series different size areas (or unequal data series the same size area). We've created a mess.

2. Loss of clarity as the stack increases.

Central banks will often have dozens of items on both the asset and liability side of their balance sheets. As each series is stacked on top of the other, volatility in a given series will by amplified across all subsequent stacked layers. This will tend to make it harder for the reader to trace out movements over time in series that are nearer to the top of the stack.

Below I've charted five data series:

Although it may not be apparent to the eye, areas A and E represent the exact same underlying data series. While the eye can easily pick out the gradual rise in A, this simply isn't possible with E. The volatility in the intervening layers B, C, and D make it impossible to pick out the fact that E is a gradually increasing data series, and that A = E.

The fix

My solution to these two problems is an interactive chart. This one shows the Federal Reserve's balance sheet since 2006:



This chart was coded in d3, an awesome javascript library created by Mike Bostock.

The first problem, squished sums, is solved by the ability to create a percent area chart. Try clicking the radio button that says "percent contribution". Rather than each series being assigned an absolute amount, they will now be scaled by their proportional contribution to the total balance sheet. This normalizes pre-QE and post QE data, thereby allowing for comparisons over both periods.

The second problem, the loss of clarity as the stack increases, is solved in two ways. By choosing the unstacked radio button, the chart will drop all data series to a resting position on the x-axis. The volatility of one series can no longer reduce the clarity of another series. This causes some busyness, but the viewer can reduce this clutter by clicking on the legend labels, removing data series that they are not interested until they've revealed a picture that tells the best story.

The loss of clarity can also be solved by leaving the chart in stacked mode, but clicking on legend labels so as to remove the more volatile data series.

There you have it. By allowing the user to 1) shift between stacked, unstacked, and percent contribution modes and 2) add and subtract data, our interactive Fed stacked area chart solves a number of problems that plague non-interactive area charts.

Addendum:

Some interesting random observations that we can pull out of our interactive area chart.

1. If you remove everything but coin (assets), you'll see that every February the Fed shows a spike in coin held. Why is that?
2. Try removing everything but items in the process of collection (assets) and deferred availability cash items (liabilities). Note the dramatic fall in these two series since 2006. The reason for this is that prior to 2001, checks were physically cleared. The Fed leased a few hundred planes which were loaded every night with checks destined for Fed sorting points. Prior to these cheques being settled, the outstanding amount in favour of the Fed was represented as items in process of collection, and those in favour of member banks be deferred availability items. The arrival of digital check technology has reduced the time over which checks remain unsettled, and thus reduced these balance sheet items to a fraction of their previous amounts. Timothy Taylor has a good post on this subject.
3. Unstacking the assets data shows that unamortized discounts/premiums represent the third largest contributor to Fed assets, up from almost nothing back in 2006. Basically, the Fed has been consistently buying large amounts of bonds via QE at a price above their face value. This premium gets added to the unamortized premium category.

1,682 days and all's well

1,682 is the number of days that the Dow Jones Industrial Average has spent rising since hitting rock bottom back in March 6, 2009.

It also happens to be the number of days between the Dow's July 8, 1932 bottom and its March 10, 1937 top. From that very day the Dow would begin to decline, at first slowly, and then dramatically from August to November when it white-knuckled almost 50%, marking one of the fastest bear market declines in history.

Comparisons of our era to 1937 seems apropos. Both eras exhibit near zero interest rates, excess reserves, and a tepid economic recovery characterized by chronic unemployment. Are the same sorts of conditions that caused the 1937 downturn likely to arise 1,682 days into our current bull market?

The classic monetary explanation for 1937 can be found in Friedman & Schwartz's Monetary History. Beginning in August 1936, the Fed announced three successive reserve requirement increases, pushing requirements on checking accounts from 13% to 26% (see chart below). The economy began to decline, albeit after a lag, as banks tried vainly to restore their excess reserve position by reducing lending and selling securities. A portion of the reserve requirement increase was rolled back on April 14, 1938, too late to prevent massive damage being done to the economy. The NBER cycle low was registered in June of that year.

Friedman & Schwartz's second monetary explanation for 1937 has been fleshed out by Douglas Irwin (pdf)(RePEc). In December 1936, FDR began to sterilize foreign inflows of gold and domestic gold production (see next paragraphs for the gritty details). This effectively froze the supply of base money, which had theretofore been increasing at a rate of 15-20% or so a year. Tight money, goes the story, caused the economy to plummet, a decline mitigated by FDR's announcement on February 14, 1938 to partially desterilize (and therefore allow the base to increase again, with limits), further mitigated by an all-out cancellation of the sterilization campaign that April.

Here are the details of how sterilization worked. (If you find the plumbing of central banking tedious, you may prefer to skip to the paragraph that begins with ">>" — I'll bring the 1937 analogy back to 2013 after I'm done with the plumbing). In the 1920s, the supply of base money could be increased in several ways. First, Fed discounting could do the trick, whereby new reserves were lent out upon appropriate collateral. The Fed could also create new reserves and buy either government securities in the open market or bankers acceptances. Lastly, gold was often sold directly to the Fed in exchange for base money. After 1934, all but the last of these four avenues had been closed. Both the Fed's discount rate and its buying rate on acceptances was simply too high to be attractive to banks, and the practice of purchasing government securities on the open market had long since petered out. Only the gold avenue remained.

New legislation in 1934 meant that all domestic gold and foreign gold inflows had to be sold to the Treasury at $35/oz. The Secretary of the Treasury would write the gold seller a cheque drawn on the Treasury's account at the Fed, reducing the Treasury's balance. The Treasury would then print off a gold certificate representing the number of ounces it had purchased, deposit the certificate at the Fed, and have the Fed renew its account balance with brand-spanking new deposits. Put differently, gold certificates were monetized. As the Treasury proceeded to pay wages and other expenses out of its account during the course of business, these new deposits were injected into the banking system.

You'll notice that by 1934 the Treasury, and not the Fed, had become responsible for increasing the base money supply, a situation that may seem odd to us today. As long as the Treasury Secretary continuously bought gold and took gold certificates representing those ounces to the Fed to be monetized, the supply of base money would increase one-for-one as the Treasury drew down its account at the Fed.

The Treasury's decision to sterilize gold inflows in December 1936 meant that although it would continue to purchase gold, it would cease bringing certificates to the Fed to be monetized. The Treasury would pay for each newly mined gold ounce and incoming foreign ounces by first transferring tax revenues and/or the proceeds of bond issuance to its account at the Fed. Only then could it afford to make the payment. Whereas the depositing of gold certificates by the Treasury had resulted in the creation of new base money, neither the transfer of tax revenues nor the proceeds of bond issuance to the Treasury's account would have resulted in the creation of new base.

FDR's sterilization campaign therefore froze the base. Gold was kept "inactive" in Treasury vaults, as Friedman & Schwartz would describe it. The moment the sterilization campaign was reversed (partially in February 1938, and fully in April), certificates were once again monetized, the base began to expand again, and a rebound in stock prices and the broader economy followed not long after.

>> Let's bring this back to the present. Before 2008 the Fed typically increased the supply of base money as it defended its target for the federal funds rate. The tremendous glut of base money created since 2008 and the introduction of interest-on-reserves has given the Fed little to defend, thus shutting the traditional avenue for base money increases. Just as the gold avenue became the only way to increase the base in 1936, quantitative easing has become the only route to get base money into the banking system. With that analogy in mind, FDR's 1936 sterilization campaign very much resembles an end to QE, doesn't it? Both actions freeze of the monetary base. Likewise, last September's decision to avoid tapering is analogous to the 1938 decision to cease sterilization (or to "desterilize") —both of these decisions unfreeze the base.

Who cares if the base is frozen? After all, in 1937 and today, any pause in base creation won't change the fact that there is already a tremendous glut in reserves. A huge pile of snow remains a huge pile, even after it has stopped snowing.

One reason that desterilization and ongoing QE might be effective is because they shape expectations about future monetary policy, and these expectations are acted upon in the present. For instance, say that the market expects the glut of base money to be removed five years in the future. Only then will reserves regain their rare, or "special" status. While a sudden announcement to taper or sterilize will do little to reduce the present glut, it might encourage the market to move up the expected date of the glut's removal by a year or two. Which will only encourage investors in the present to sell assets for soon-to-be rare reserves, causing a deflationary decline in prices. On the other hand, a renewed commitment to QE or desterilization may extend glut-expectations out another few years. This promise of an extended glut period pushes the prospect that reserves might once again be special even further down the road. With the return on base money having been reduced, current holders of the base will react by trying to offload their stash now—thus causing a rise in prices in the present.

If the monetary theories about the 1937 recession are correct, it is no wonder then that 1,682 days into our current bull market investors seem to be so edgy about issues like tapering. Small changes in current purchasing policies may have larger effects on markets than we would otherwise assume thanks to the intentions they convey about future policy.

QE is effective insofar as it is capable of pushing market expectations concerning the future removal of the base money glut ever farther into the future. But once that lift-off point has been pushed so far off into the distant future (say ten years) that the discounted value of going further is trivial, more QE will have minimal impact.

If QE is nearing the end of its usefulness, what happens if we are hit by a negative shock in 2014? Typically when an exogenous shock hits the economy and lowers the expected return on capital, the Fed will quickly reduce the return on base money in order to ensure that it doesn't dominate the return on capital. If the base's return is allowed to dominate, investors will collectively race out of capital into base money, causing a crash in capital markets. The problem we face today is that returns on capital are currently very low and nominal interest rates near zero. Should some event in 2014 cause the expected return on capital to fall below zero, there is little room for the Fed to reduce the return on base money so as to prevent it from dominating the return on capital—especially with interest-on-reserves unable to fall below zero and QE approaching irrelevance. Come the next negative shock, we may be doomed to face an unusually sharp and quick crash in asset prices (like 1937) as the economy desperately tries to adapt to the superior return on base money.

So while I am still somewhat bullish on stocks 1,682 days into the current bull market, I am worried about the potential for contractionary spirals given that we are still at the zero-lower bound. I'm less worried about the Fed implementing something like a 1937-style sterilization campaign. Incoming Fed chair Janet Yellen is well aware of the 1937 event and is unlikely to follow the 1937 playbook. Writes Yellen:

If anything, I’m more concerned that we will be tempted to tighten policy too soon, thereby aborting recovery. That’s just what happened in 1936 when, following two years of robust recovery, the Fed tightened policy because it was worried about large quantities of excess reserves in the banking system. The result? In 1937, the economy plunged back into a deep recession.  -June 30, 2009 [link] 

---

Other recent-ish commentary on the 1937 analogy include Paul Krugman, Francois Velde (pdf), Scott Sumner, Lars Christensen, Christina Romer, Charles Calomiris (pdf), Business Insider, and David Glasner.

Visualizing alt-coins

I've been teaching myself a Javascript visualization library called D3. It gives the chart creator an incredible degree of control in making interactive web-based charts. My previous interactive charts, including my interactive Eurosystem balance sheet tool, have all used the Google Vizualization API, which is far less powerful than D3.

You may want to read my last post was on bitcoin alternatives in order to understand what I'm trying to get at in this post. In visualizing the cryptocoin market, I think it's important to convey information about both the relative size of each cryptocoin and the date on which it was born. In doing so I'm trying to illustrate how being the first mover engenders network effects -- early cryptocoins tend to attract the largest market share. I also want to capture the mini boom in new coins since May 2013. Below I've pasted a D3 visualization of this data. Users can interact with it by hovering the mouse over each circle. The code is here.

I'm sure that chart nerds will accuse me of unnecessarily using a circle chart. The areas of circles are not as easily compared by our eye as, say, lines with differing heights. A quick glance immediately picks up height differentials -- it takes more effort to pick out area differentials. Far better would be to use a chart like this:

The logarithmic scale in the above line chart adds resolution by rendering each alt-coin's bar more comparable to what would otherwise be a humongous bitcoin bar. If I had time, I'd allow the user to zoomover the busy part in 2013. The problem with this chart is that the lines get jumbled together when the births of new coins comes in bunches. In this respect, the circle chart is superior to the line chart since it can easily handle simultaneous births by overlaying the circles one on top of the other.

The other problem with my line chart is it really doesn't convey the sheer size of bitcoin. I think the circle chart is pretty successful in this respect. The blue dot that represents BTC is virtually spilling off the page. When I came up with the design for the circle chart, I was thinking about the chart below:

Bitcoin is like the sun. The alternatives are still wimpy planets.

Play with the interactive ECB balance sheet tool

For the full version, go here. The chart below only includes Eurosystem assets, not liabilities. It goes back just a few years. The full version goes back to 2000 and includes liabilities.

To remove a data series, either click on its legend label or the line on the chart. Remove as many series as you want to get a better understanding for how balance sheet items interact. This is in beta, so it may be a bit buggy. Expect redraw delays.

(May take a second or two)

Huge moves

www.financialgraphart.com

Open mic night on interest rate spreads

Ok, readers. Here's a chance for you to flex your muscles. The following chart shows various short-term interest rates:

Why are these rates all so different? Can the differentials between them be arbitraged away? What sorts of institutional rigidities might be preventing arbitrage? For instance, we know certain institutions like Fannie Mae and Freddie Mac can't get interest on reserves held at the Fed. What other sorts of fine details might be important? Or are the differentials between these various rates not currently open to arbitrage? Can they be explained by term risk? How much do other sorts of risk, like liquidity risk, counterparty risk, default risk etc drive spreads?  A few specific questions:

a) The DTCC Treasury General Financial Collateral (GCF) repo rate used to trade at or below the fed funds rate. The Treasury GCF repo rate is a collateralized rate. Since collateral reduces risk, it makes sense it would trade below the fed funds rate. But why is the riskier rate now below the safer rate?

b) Why does the Fed funds rate generally trade above the t-bill rate? There's presumably less term risk in the FF rate, which would imply a lower Fed funds rate. Does interbank risk account for the higher fed funds rate?

c) Is it a risk-free trade to fund oneself in the fed funds market and invest the proceeds overnight at the interest rate?

d) Why would banks hold t-bills at all if they can simply keep reserves at the Fed for a superior return of 0.25%? The credit risk seems similiar: as a bank, you're exposed to the Fed in the case of reserves, and the Treasury in the case of bills.

e) Sometimes the 4-week t-bill yield crosses over the 3-month. Why? The credit risk is the same, and presumably bills are equally liquid. Are these inversions purely related to expected changes in yields?

Data, ideas, links,etc all much appreciated. I'm sure I'll have more questions in the comments, or if you have other interesting observations, go for it.

[Update 22/03/2013: I reinputted the Treasury GCF rate since my original data was off]

Having fun with bear markets

Here's a fun tool you can play around with. You may have to download the Flash player:



I made this chart back in 2009 but never quite finished it. A few days ago I decided to get 'er done, but when I opened the old document the dismal realization hit me that I had completely forgotten how to make charts in Adobe Flash. What a slog the last 46 hours have been. Anyways, enjoy.

The original is available here if you want to use it in your own posts, or if Blogger of  Google Reader won't play it for you.

Bank of Japan balance sheet

Other central bank balance sheets I've illustrated include that of the Bank of Canada, Federal Reserve, and People's Bank of China.

Making these charts reminds me of a great xkcd cartoon. 

The feeling of hyperinflation illustrated

I listened to a good Econtalk podcast last night with guest Steve Hanke. Few people in the world know as much as Steve does about hyperinflation. His catalogue of 56 hyperinflations (with Nicholas Krus) inspired me to do this chart. Most of us have been lucky enough not to have lived through hyperinflation. Here's what it might feel like if we did.

Data visualization: The US - From oil importer to oil exporter?

The US is currently importing significantly less crude oil and crude oil products than it did in 2005. Now if you were listening to the Presidential debates, then you probably heard Barack Obama take credit for this improvement. But the real driver has been improvements in technology, namely fracking and horizontal drilling. The chart below disaggregates the flow of petroleum into its constituent parts.

The US is certainly importing less crude oil than seven years ago. It is also now exporting significant quantities of refined crude products. The largest contributor to this shift comes from the distillate/diesel category. A lot of this diesel is going Rotterdam and from there to the rest of Europe. The switch from importing to exporting products isn't confined to diesel though, note how almost all the black arrows in the products section are now red.

Data visualization: The People's Bank of China balance sheet

David Glasner and Scott Sumner have posts on Chinese monetary policy. They both inquire about the People's Bank of China (PBoC) balance sheet. I've affixed a chart of it below.

Here's a quick rundown of how the PBoC balance sheet changes. The PBoC sets the yuan-to-dollar exchange rate at some rate below what it would in a free market. Chinese exporters thereby enjoy a subsidy. The law requires that the foreign currency that exporters earn overseas be repatriated and exchanged for yuan. The PBoC prints yuan (bottom green area) or provides deposits (bottom purple area), receiving this foreign exchange in return (top green area).

(scribd pdf)

By creating such large quantities of liquid currency and reserves, the PBoC will force the domestic price level  to rise. In order to prevent this inflation, the Bank must "sterilize", or mop up the liquidity it has created. It does this by issuing bonds (dark blue area at bottom) to domestic banks in exchange for currency and reserves (bottom purple and green). Thus liquid instruments are replaced by an illiquid instrument, bonds. The PBoC also forces banks to hold large quantities of required reserves (bottom purple area), which immobilizes what would otherwise be a fairly liquid instrument. In this way the rise in the domestic price level can be temporarily prevented. The PBoC could also sterilize by selling domestic assets (top pink, blue, or yellow areas) and retiring the currency and reserves it receives. But given that domestic assets held on the PBoC balance sheet haven't changed much over the years, it's likely that different means are being found to sterilize.

A visual review of the lending facilities created by the Fed during the credit crisis

I'm currently updating my History of the Fed chart. As a side project, here's what's happened to the various Federal Reserve credit programs initiated during the crisis. Most of them have rolled off the Fed's balance sheet. Even the most toxic of them - Maiden Lane I and III - seem set to be paid off.

Go to scribd to see a higher resolution pdf. Alternatively, my public gallery has a high-res GIF.

This chart illustrates one role of a central bank, that of lender of last resort role. A central banking facing a crisis is supposed to lend to everyone on any sort of collateral and buy all sorts of assets. If you read through the fine print of the chart, you'll see that the Fed's new facilities accepted a broad range of assets - from commercial paper to CDOs to RMBS, and opened themselves up to a fairly wide array of counterparties.

What is really happening here is that the Fed is providing liquidity insurance. Liquidity insurance is like any other form of insurance - home insurance, car insurance, credit default insurance, whatever. Given the possibility of a fire, people buy house insurance to compensate  for that outcome. Given the possibility that one might be required to do a fire-sale into a thin market, it might be a good idea to purchase liquidity insurance ahead of time. Both are products that can be provided by insurance companies competing in the market.

Unfortunately the Fed can never know if it is providing liquidity insurance at the right price because it is the monopoly provider and has no competition. During the credit crisis, a lot of firms were extended liquidity insurance by the Fed even though they never paid for it ahead of time. In the future, one would hope that the free market takes over the Fed's role of liquidity insurance provider, leaving the Fed to operate the clearing system and set a few interest rates.

Data visualization: The size of major bull markets

Barry Ritholtz at The Big Picture spotlighted my most recent chart, "The size of major bull markets." You can purchase it on paper format here. While the improvement in GDP and employment since 2009 has been tepid, you can't complain about the stock market's performance. That being said, the current rally pales in comparison to the speed and vigor of the 1933-37 rally. Thoughts? Comments?

Data visualization: breaking down The Economist's classic chart style

Data visualization: History of bear markets

By yours truly:

scribd version