Tag Archives: stock market

Bitcoin risks, uses, and bubble

Bitcoin prices over the last 3 years

Bitcoin prices over the last 3 years

As I write this, the price of a single bitcoin stands are approximately $11,100 yesterday, up some 2000% in the last 6 months suggesting it is a financial bubble. Or maybe it’s not: just a very risky investment suited for inclusion in a regularly balanced portfolio. These are two competing views of bitcoin, and there are two ways to distinguish between them. One is on the basis of technical analysis — does this fast rise look like a bubble (Yes!), and the other is to accept that bitcoin has a fundamental value, one I’ll calculate that below. In either case, the price rise is so fast that it is very difficult to conclude that the rise is not majorly driven by speculation: the belief that someone else will pay more later. The history of many bubbles suggests that all bubbles burst sooner or later, and that everyone holding the item loses when it does. The only winners are the last few who get out just before the burst. The speculator thinks that’s going to be him, while the investor uses rebalancing to get some of benefit and fun, without having to know exactly when to get out.

That bitcoin is a bubble may be seen by comparing the price three years ago. At that point it was $380 and dropping. A year later, it was $360 and rising. One can compare the price rise of the past 2-3 years with that for some famous bubbles and see that bitcoin has risen 30 times approximately, an increase that is on a path to beat them all except, perhaps, the tulip bubble of 1622.

A comparison between Bitcoin prices, and those of tulips, 1929 stocks, and other speculative bubbles; multiple of original price vs year from peak.

A comparison between Bitcoin prices, and those of tulips, 1929 stocks, and other speculative bubbles; multiple of original price vs year from peak.

That its price looks like a bubble is not to deny that bitcoin has a fundamental value. Bitcoin is nearly un-counterfeit-able, and its ownership is nearly untraceable. These are interesting properties that make bitcoin valuable mostly for illegal activity. To calculate the fundamental value of a bitcoin, it is only necessary to know the total value of bitcoin business transactions and the “speed of money.” As a first guess, lets say that all the transactions are illegal and add up to the equivalent of the GDP of Michigan, $400 billion/year. The value of a single bitcoin would be this number divided by the number of bitcoin in circulation, 12,000,000, and by the “speed of money,” the number of business transactions per year per coin. I’ll take this to be 3 per year. It turns out there are 5 bitcoin transactions total per year per coin, but 2/5 of that, I’ll assume, are investment transactions. Based on this, a single bitcoin should be worth about $11,100, exactly its current valuation. The speed number, 3, includes those bitcoins that are held as investments and never traded, and those actively being used in smuggling, drug-deals, etc.

If you assume that the bitcoin trade will grow to $600 billion year in a year or so, the price rise of a single coin will surpass that of Dutch tulip bulbs on fundamentals alone. If you assume it will reach $1,600 billion/year, the GDP of Texas in the semi-near future, before the Feds jump in, the value of a coin could grow to $44,000 or more. There are several problems for bitcoin owners who are betting on this. One is that the Feds are unlikely to tolerate so large an unregulated, illegal economy. Another is that bitcoin are not likely to go legal. It is very hard (near impossible) to connect a bitcoin to its owner. This is great for someone trying to deal in drugs or trying hide profits from the IRS (or his spouse), but a legal merchant will want the protection of courts of law. For this, he or she needs to demonstrate ownership of the item being traded, and that is not available with bitcoin. The lack of good legitimate business suggests to me that the FBI will likely sweep in sooner or later.

Yet another problem is the existence of other cryptocurrencies: Litecoin (LTC), Ethereum (ETH), and Zcash (ZEC) as examples. The existence of these coins increase the divisor I used when calculating bitcoin value above. And even with bitcoins, the total number is not capped at 12,000,000. There are another 12,000,000 coins to be found — or mined, as it were, and these are likely to move faster (assume an average velocity of 4). By my calculations, with 24,000,000 bitcoin and a total use of $1,600 billion/year, the fundamental value of each coin is only $16,000. This is not much higher than its current price. Let the buyer beware.

For an amusing, though not helpful read into the price: here are Bill Gates, Warren Buffet, Charlie Munger, and Noam Chomsky discussing Bitcoin.

Robert Buxbaum, December 3, 2017.

The Gift of Chaos

Many, if not most important engineering systems are chaotic to some extent, but as most college programs don’t deal with this behavior, or with this type of math, I thought I might write something on it. It was a big deal among my PhD colleagues some 30 years back as it revolutionized the way we looked at classic problems; it’s fundamental, but it’s now hardly mentioned.

Two of the first freshman engineering homework problems I had turn out to have been chaotic, though I didn’t know it at the time. One of these concerned the cooling of a cup of coffee. As presented, the coffee was in a cup at a uniform temperature of 70°C; the room was at 20°C, and some fanciful data was presented to suggest that the coffee cooled at a rate that was proportional the difference between the (changing) coffee temperature and the fixed room temperature. Based on these assumptions, we predicted exponential cooling with time, something that was (more or less) observed, but not quite in real life. The chaotic part in a real cup of coffee, is that the cup develops currents that move faster and slower. These currents accelerate heat loss, but since they are driven by the temperature differences within the cup they tend to speed up and slow down erratically. They accelerate when the cup is not well stirred, causing new stir, and slow down when it is stirred, and the temperature at any point is seen to rise and fall in an almost rhythmic fashion; that is, chaotically.

While it is impossible to predict what will happen over a short time scale, there are some general patterns. Perhaps the most remarkable of these is self-similarity: if observed over a short time scale (10 seconds or less), the behavior over 10 seconds will look like the behavior over 1 second, and this will look like the behavior over 0.1 second. The only difference being that, the smaller the time-scale, the smaller the up-down variation. You can see the same thing with stock movements, wind speed, cell-phone noise, etc. and the same self-similarity can occur in space so that the shape of clouds tends to be similar at all reasonably small length scales. The maximum average deviation is smaller over smaller time scales, of course, and larger over large time-scales, but not in any obvious way. There is no simple proportionality, but rather a fractional power dependence that results in these chaotic phenomena having fractal dependence on measure scale. Some of this is seen in the global temperature graph below.

Global temperatures measured from the antarctic ice showing stable, cyclic chaos and self-similarity.

Global temperatures measured from the antarctic ice showing stable, cyclic chaos and self-similarity.

Chaos can be stable or unstable, by the way; the cooling of a cup of coffee was stable because the temperature could not exceed 70°C or go below 20°C. Stable chaotic phenomena tend to have fixed period cycles in space or time. The world temperature seems to follow this pattern though there is no obvious reason it should. That is, there is no obvious maximum and minimum temperature for the earth, nor any obvious reason there should be cycles or that they should be 120,000 years long. I’ll probably write more about chaos in later posts, but I should mention that unstable chaos can be quite destructive, and quite hard to prevent. Some form of chaotic local heating seems to have caused battery fires aboard the Dreamliner; similarly, most riots, famines, and financial panics seem to be chaotic. Generally speaking, tight control does not prevent this sort of chaos, by the way; it just changes the period and makes the eruptions that much more violent. As two examples, consider what would happen if we tried to cap a volcano, or provided  clamp-downs on riots in Syria, Egypt or Ancient Rome.

From math, we know some alternate ways to prevent unstable chaos from getting out of hand; one is to lay off, another is to control chaotically (hard to believe, but true).