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Showing posts with label Finance. Show all posts

Fama Portfolio

The Fama Portfolio, is a new book from the University of Chicago Press. This is a collection of Gene Fama's papers, edited by Toby Moskowitz and me. It includes introductory essays by a group of Gene's distinguished colleagues, Ken French, Bill Schwert, René Stulz, Cliff Asness, John Liew, Campbell Harvey, Jan Liu, Amit Seru, and Amir Sufi.

The essays explain the ideas in modern terms, tell you why the papers are important, explain how the papers influenced subsequent thinking, update you on where our understanding on each point is today, and speculate about where new ideas may go. The continuing vitality of this work, even parts decades old, is impressive.

The task was hard. Which Fama papers should one read? Well, all of them! but we nonetheless had to pick. We typically chose a famous one from early in one of Gene's many research programs, and then a less known later one that really sums it up clearly. Gene's ideas get clearer over time, just like the rest of ours do.

The press lets us post our essays.  Here are mine (most joint with Toby):

  1. Preface;
  2. Efficient Markets and Empirical Finance
  3. Luck vs. Skill;
  4. Risk and Return
  5. Return Forecasts and Time Varying Risk Premiums
  6. Our Colleague.
Other authors may post their essays on their webpages. Otherwise, you'll just have to buy the book!

The contents:


Preface, by John H. Cochrane and Tobias J. Moskowitz
I. Introductions
My Life in Finance
Eugene F. Fama
Things I’ve Learned from Gene Fama
Kenneth R. French
Gene Fama’s Impact: A Quantitative Analysis
G. William Schwert and René M. Stulz
II. Efficient Markets
Efficient Markets and Empirical Finance
John H. Cochrane and Tobias J. Moskowitz
The Great Divide
Clifford Asness and John Liew
Efficient Capital Markets: A Review of Theory and Empirical Work
Eugene F. Fama
Efficient Capital Markets: II
Eugene F. Fama
Market Efficiency, Long-Term Returns, and Behavioral Finance
Eugene F. Fama
III. Efficiency Applied: Event Studies and Skill
Fama, Fisher, Jensen, and Roll (1969): Retrospective Comments
Ray Ball
Eugene Fama and Industrial Organization
Dennis W. Carlton
The Adjustment of Stock Prices to New Information
Eugene F. Fama, Lawrence Fisher, Michael C. Jensen, and Richard Roll
Luck versus Skill
John H. Cochrane and Tobias J. Moskowitz
Luck vs. Skill and Factor Selection
Campbell R. Harvey and Yan Liu
Luck versus Skill in the Cross-Section of Mutual Fund Returns
Eugene F. Fama and Kenneth R. French
IV. Risk and Return
Risk and Return
John H. Cochrane and Tobias J. Moskowitz
Risk, Return, and Equilibrium: Empirical Tests
Eugene F. Fama and James D. MacBeth
The Cross-Section of Expected Stock Returns
Eugene F. Fama and Kenneth R. French
Common Risk Factors in the Returns on Stocks and Bonds
Eugene F. Fama and Kenneth R. French
Multifactor Explanations of Asset Pricing Anomalies
Eugene F. Fama and Kenneth R. French
V. Return Forecasts and Time-Varying Risk Premiums
Return Forecasts and Time Varying Risk Premiums
John H. Cochrane
Short-Term Interest Rates as Predictors of Inflation
Eugene F. Fama
Forward Rates as Predictors of Future Spot Rates
Eugene F. Fama
Forward and Spot Exchange Rates
Eugene F. Fama
Dividend Yields and Expected Stock Returns
Eugene F. Fama and Kenneth R. French
The Information in Long-Maturity Forward Rates
Eugene F. Fama and Robert R. Bliss
VI. Corporate Finance and Banking
Corporate Finance
Amit Seru and Amir Sufi
Agency Problems and the Theory of the Firm
Eugene F. Fama
Separation of Ownership and Control
Eugene F. Fama and Michael C. Jensen
Dividend Policy: An Empirical Analysis
Eugene F. Fama and Harvey Babiak
Disappearing Dividends: Changing Firm Characteristics or Lower Propensity to Pay?
Eugene F. Fama and Kenneth R. French
Financing Decisions: Who Issues Stock?
Eugene F. Fama and Kenneth R. French
Banking in the Theory of Finance
Eugene F. Fama
Conclusion: Our Colleague, by John H. Cochrane and Tobias J. Moskowitz
Contributors
 

Buybacks

A short oped for the Wall Street Journal here  on stock buybacks. As usual, they ask me not to post the whole thing for 30 days though you can find it ungated if you search. An excerpt:
... Buybacks do not automatically make shareholders wealthier. Suppose Company A has $100 cash and a factory worth $100. It has issued two shares, each worth $100. The company’s shareholders have $200 in wealth.  Imagine the company uses its $100 in cash to buy back one share. Now its shareholders have one share worth $100, and $100 in cash. Their wealth remains the same.
Wouldn’t it be better if the company invested the extra cash? Wasn’t that the point of the tax cut? Perhaps. But maybe this company doesn’t have any ideas worth investing in. Not every company needs to expand at any given moment.
Now suppose Company B has an idea for a profitable new venture that will cost $100 to get going. The most natural move for investors is to invest their $100 in Company B by buying its stock or bonds. With the infusion of cash, Company B can now fund its venture.
 [Left out: The alternative would be for company A to lend the money to company B or to buy its stock. But why are the managers of company A, out of its own ideas, better than its investors at spotting other companies with new projects to invest the stockholders’ money?]
The frequent rise in stock price when companies announce buybacks proves the point. In my example, Company A’s share price stays fixed at $100 when it buys back a share. But suppose before the buyback investors were nervous the company would waste $40 of the $100 cash. Imagine an overpriced merger or excessive executive bonuses. Not every investment is wise! 
The $100, stuck inside Company A, would be valued by the market at $60 and the company’s total value would be $160, or $80 a share. If it spent the $100 to buy back one share, the other share would rise from $80 to $100, the value of its good factory. 
When a company without great ideas repurchases shares, the price of the remaining shares rise. This stock price rise is no gift to shareholders. It is just the market’s recognition that $100 has been saved from inefficient investment.
Full oped in 30 days.

Update: 

Based on follow up commentary, it's pretty clear than 99% of people do not understand the point: It's not about what companies do with today's profits. The case for buybacks is not that cash must chase investment. The point of the tax cut is the profitability of new investment. Without that, somebody will still just sit on the cash. With that, money will find its way to new investment. Otherwise, we're just putting money from the right pocket to the left pocket. Investment in the end comes when it is profitable, looking forward. Nothing about who gets what part of today's profits has anything to do with it. I will stress this next time! A good learning experience.

Tyler Cowen has a good Bloomberg View focusing on this point, my emphasis:
A basic principle of economic reasoning is to think in terms of real resources, not just the first-round flows of money. If a major corporation engages in buybacks, that simply transfers money from one set of hands to another -- from the corporate entity to the shareholders. It doesn’t destroy real resources or determine their final disposition. The money could still go to a venture capital fund, or into private equity or a real estate investment trust, in addition to numerous other undertakings, all of which might boost investment and real wages.

Tremors

A debt crisis does not come slowly and predictably. This year's short term bond holders, a very risk averse lot, are mostly interested in whether next year, new bondholders will show up, to lend the government money to pay this year's bondholders back. Bondholders can run on small jitters over that expectation.

When bondholders get nervous, they demand higher interest rates. More than higher interest rates, they diversify their portfolios, or just refuse. Debt gets "hard to sell" at any price. A different class of bondholders, willing to take risks for better rates, must come in to replace the safety-oriented clientele that currently holds short-term government debt.

As interest rates rise, interest costs on the debt rise. At $20 trillion of debt, when interest rates rise to 5%, interest costs rise to $1 trillion dollars, essentially doubling the deficit. That makes markets more nervous, they demand even higher interest rates, and when that spiral continues, you have a full blown debt crisis on your hands.

Short term debt compounds the problem. Since the US has borrowed very short term, interest increases make their way to the budget more quickly. If the US had borrowed everything in 30 year bonds, the spiral mechanism from higher rates to higher deficits would be cut off.

The crisis typically comes in bad times -- when in a war, recession, or financial crisis, the government suddenly needs to borrow a lot more and markets doubt its ability to repay.

But there is a case for a crisis to happen in good times as well. We have known for decades that the fundamental US problem is promised entitlement spending far beyond what our current tax system can fund. Markets have, sensibly I think, presumed that the US would fix this problem sooner or later. It's not that hard as a matter of economics. Well, say markets in 2005, OK for now, you have a war on terror and a war in Iraq on your hands, we'll trust you to fix entitlements later. Well, say markets in 2012, OK for now, you're recovering from a massive financial panic and great recession. We'll trust you to fix entitlements later, and we'll even lend you another $10 trillion dollars. But what's our excuse now? At 4% unemployment, after 8 years of uninterrupted growth, if we can't sit down now and solve the problem, when will we? Markets have a right to think perhaps America is so fractured we won't be able to fix this in time. Or, more accurately, markets have a right to worry that next year's markets will have that worry, and get out now.

All this is well known, and most commenters including me think that day is in the future. But the future comes often quicker than we think.

With that prelude, two pieces of news strike me as distant early warning signs. Here, from Torsten Sløk's excellent email distribution are two graphs of the bid-to-cover ratio in Treasury auctions.



Torsten's interpretation:

The first chart below shows that the bid-to-cover ratio at 4-week T-bill auctions is currently at the lowest level in almost ten years.... demand is also structurally weaker when you look at 10-year auctions, see the second chart. The main risk with issuing a lot of short-dated paper such as 4-week T-bills is that in 4 weeks it all needs to be rolled over and added to new issuance in the pipeline. In other words, the more short-dated paper is issued, the bigger the snowball in front of the US Treasury gets. 
Things are so far looking ok, but the risks are rising that the US could have a full-blown EM-style fiscal crisis with insufficient demand for US government debt, and such a loss of confidence in US Treasury markets would obviously be very negative for the US dollar and US stocks and US credit. The fact that this is happening with a backdrop of rising inflation is not helpful. Investors in all asset classes need to watch very carefully how US Treasury auctions go for any signs of weaker demand.
The last part is the mechanism I described above. As an ivory tower economist, I tend to overlook such technical issues. If the bid to cover ratio is low, well, then that just means we need higher rates. But higher rates aren't a panacea as above, since higher rates make paying it back harder still. As I look at debt crises, also, it isn't just a matter of higher rates. There comes a point that the usual people aren't buying at all.

Again, we're not there yet, and I think we have a long way to go. But this is a little rumble.

The second tremor is Why International Investors Aren’t Buying U.S. Debt in the Wall Street Journal.  The overall message is also that international investors are getting nervous.

US 10 year yields are 2.9% already. German yields are 0.68%. Why aren't people buying our debt? Well, number one, they are worrying a further slide in the dollar. Which comes when next year's international bond holders really don't want to hold US debt.

Most of the article is.. well, difficult for this former finance professor to follow. The article claims that one used to be able to lock in the difference, "Last year, buying Treasurys and swapping the proceeds back into euros provided European investors with a higher return than buying German sovereign bonds."[my emphasis] This sounds like arbitrage, "covered interest parity violations." That arbitrage is not perfect, but my impression is that it's not whole percentage points either. And you really can't lock in 10 years of funding. Besides which, someone else is on the risk-taking side of the swap. So the interviewed traders must be only partially hedging the difference. Perhaps it's really "uncovered interest parity," where you borrow Europe 0.68% invest in the US 2.9% and pray or only partially hedge the exchange rate risk. (On that, "The New Fama Puzzle by Matthieu Bussiere, Menzie D. Chinn, Laurent Ferrara, Jonas Heipertz, blog post at econbrowser documents that uncovered interest parity, where you invest in the high yield currency and take the risk, is losing its profitability. Interest spreads seem to correspond to future exchange rate changes after all.)

All to follow up on for another day. Mostly, it rang a bell as a little tremor that people who answer WSJ reporter's phone calls are expressing nervousness about US debt.

Again, these are little rumbles. I still think that a full blown crisis will come only amid a large international crisis, featuring some big country defaults (Italy?), big financial trouble in China, perhaps a war, state and local pension failures, and the US comes to markets with unresolved entitlements and asks for another $10 trillion. But I could be wrong. We live on an earthquake fault of debt, and the one thing I know from my own past forecasting ability (I have lived through 1987, the dot com boom and bust, 2008, the recent boom, and more, and saw none of them coming in real time) that I will not see it coming either.

Update:  Reply to Benjamin Cole, below. The US has never spent less on defense, as a fraction of GDP or of the federal budget, than it is doing today, since the 1930s. Here is defense / GDP. Defense / federal budget is even less, as the budget has expanded as a share of GDP.



Stock Gyrations

Is this 1929, the beginning of the end? Or 2007? Is it 1974, annus horribilis in which the stock market drifted down 40% having something to do with stagflation, and did not recover until the 1980s? Is it 1987, a quick dip followed by recovery in a year? Or just an extended version of the flash crash, when the market went down 10% in a few hours, and bounced back by the end of the day? Are we in a "bubble" that's about to burst? How much does this have to do with the Fed? Of course I don't know the answer, but we can think through the logical possibilities.

(Note: This post has equations, graphs and quotes that tend to get mangled when it gets picked up. If it's mangled, come back to the original here.)

Why do prices fall?

Stock prices fall when there is bad news about future profits, or when the discount rate rises.

The discount rate is the rate investors require, looking forward, to get them to buy stocks. If people require a better rate of return, with no change in their expected cashflows, prices drop.

Stop and think about that a second, as it's counterintuitive. Yes, the only way to get a better return out of the same profits or dividends is for today's price to drop.

Another way to think about it: Suppose all of a sudden there are good profitable opportunities for your money -- bond interest rates rise, or it's a good time to take money out of markets and invest in your company. Well, people will try to move money to those alternatives. But the stock market is a hot potato; someone has to hold the stocks. So stock prices must decline until the rate of return going forward matches the other attractions on a risk-adjusted basis. Good news about returns going forward is bad news about a downward jump in stock prices.

Bad news about cashflows is, well, bad news. The dashed line shifts down. Your stocks are not going to pay off as well as before. Higher required returns are neutral, really, for long-term investors. The price drops today, but the higher returns mean the price will slowly recover, just as long-term government bonds do.

So is this a moment of bad cashflow news or higher discount rate?  Most commentary suggests it's not bad news about cashflows. The economy seems finally to be growing, and there isn't anything like a brewing subprime or other problem, as there was in 2007. Maybe we don't know about it, but one certainly doesn't read about it.

So let's think about discount rates. Why might investors require a higher return on stocks? Is it interest rates, a risk premium, and is the Fed behind it all?

Where are we? 

Are we  in a "bubble'' that is about to pop? Let's start by reviewing some facts. Here is the cumulative return on the NYSE since 1990. (This is the CRSP NYSE. Sadly the data stops 12/31/2017 so I don't show the recent drop. The larger index including NASDAQ shows a larger rise and fall in the tech boom and bust, but is otherwise about the same.)
Cumulative return NYSE since 1990. Source CRSP
This graph does not show anything terribly unusual about the recent period. Stocks drift up during expansions, and take a beating in recessions. There are also little blips like the Krugman election panic of November 2016. (Sorry, I couldn't resist.)  Why have stocks gone up so much? Well, mostly because the expansion has gone on so long. The recent period is also notable in that the little wiggles are much smaller -- less volatility. That ended last week too.

Update: Thanks to Torsten Slok at DB the last year follows. His point, it's sharp but not all that big.



Next, look at the price-dividend ratio. (For a variety of reasons this is a better valuation measure than the commonly used price earnings ratio. This (CRSP) measure of dividends includes all cash payment to shareholders. No, repurchases don't cause a problem.)

Price / dividend ratio, NYSE. Source CRSP
You can see prices were high relative to dividends in the booming 1960s; they really rose in the late 1990s before the big 2000 bust. Then you see the 2008 crisis and recovery, and more recent wiggles. You can see prices fall in recessions, even relative to dividends which also fall in recessions.

Where is the booming stock market? Stock prices relative to dividends have not grown at all since the end of the recession.  Well, evidently, dividends have been rising just as fast as prices in the current expansion -- which again weren't rising all that fast anyway. So the main reason stock prices are high is that dividends are high, and people expect that slow growth to continue.

So here we were before the recent drop. Are prices too high? Well, not as much as in 1999 for sure! But P/D is a lot higher than historical norms.  Is this the beginning of a drop back to historic levels like 30, or even 20? Or is this a new normal? There is way too much commentary lately that whatever we remember from 20 years ago was "normal" and that things have to go back to that. Not without a reason.

Interest rates and stock prices 

To think about this question we need some basics of what determines price-dividend ratios. Over long time periods, the return you get on stocks is the dividend yield -- how many dividends they pay per dollar invested plus the growth in dividends. Over short time periods you also get price appreciation per dividend, but over long time periods, the ratio of price to dividends comes back and price growth is the same as dividend growth.  In sum,

return = dividend yield + growth rate
\[ r = \frac{D}{P} + g \]This is also where price comes from. The price you're willing to pay depends on the expected return going forward, and expected  dividend growth (Prices are high relative to current dividends if people expect a lot more dividends in the future.)\[  \frac{D}{P}  = r - g = r^l + r^e - g \]\[  \frac{P}{D}  =\frac{1}{r - g} =\frac{1}{ r^l + r^e - g}  \] Here I broke apart the expected return into components. First, the expected return on stocks is equal to the long-term real risk-free rate \(r^l\) plus the risk premium \(r^e\). This is just a definition -- the risk premium is \(r^e=r-r^l\).

So, looked at either as D/P or P/D, we now have the tools to think about what pushes stock prices around.

(There is nothing inherently ``rational'' or ``efficient markets'' about this. Behavioral finance just says the expectations are wrong, for example that people think \(g\) is big when in fact \(r\) is small.)

Stock prices are very sensitive to real interest rates, risk premiums, and growth expectations. At our current P/D of 40, for example, this means \(r-g=1/40=0.025\) or 2.5%. Just half a percent change  in expected return or growth rate, \(r-g=0.02\) would mean \(P/D=1/0.02=50\), a 25% rise in stock prices. Conversely, a half percent rise in real interest rates would mean \(r-g=0.03\), a decline to \(P/D=33\) a 16.7% fall.  No wonder stocks are (usually) volatile!

Now, to what's going on? If we take growth rate expectations off the table, then stock prices are moving because of changes in interest rates. And small interest rate changes do indeed imply big stock valuation changes -- though, again, take heart because it means the rate of return is higher, as in the first picture.

Does this relationship hold historically? Here is the D/P ratio (P/D upside down) and a measure of long-term real interest rates.
NYSE D/P, Cleveland Fed 10 Year real rate, and 10 year TIPS

(The problem with 10 year real rates is knowing what 10 year expected inflation is, given that we did not have TIPS. There are lots of other problems too, such as unwinding the liquidity premium in government bonds. Here I used the Cleveland Fed's real rate model, which is in part based on survey expectations. I added the 10 year TIPS yield where we have it to confirm the general pattern of the Cleveland Fed's calculation.)

This is a remarkable graph: The entire rise in valuations from 1980 to 2008 corresponds exactly to the decline in real interest rates.

By this measure, the decline in real rates was huge, from 7% to essentially 0%. Plug that in to \(P/D=1/(r-g)\) and we're done. Stock prices are exactly where they should be.

In fact, by this measure, stock prices are too low. In 2008, real rates kept right on trundling down another two percentage points, but the dividend yield stabilized.

Well, I was careful to say "corresponds to" not "caused by" for a reason. The risk premium and growth expectations changed as well. Arguably the move to a low-growth economy starting in 2000, cutting one to two percentage points off \(g\), offset the decline in real rate. Or perhaps the risk premium isn't as low as we think it is. This isn't just waffling -- the relationship is basically an identity. One of those options must be true. If the dividend yield is 2.5%, and the real interest rate is 0%, then \(r^e-g\) is 2.5%, and has grown since 2000. Either the risk premium has grown 2.5% -- so much for the ``low risk premium'' -- or growth expectations have fallen 2.5%. Or the long-term real rate is profoundly mismeasured here.

More on all this in a minute. But the graph reminds us 1) Real rates have come down a lot, and 2) persistent changes in real rates really are an important part of stock market valuations. Oh, and they have nothing to do with ``risk appetite'' and all that other blather. Stocks are valued like bonds plus risk. We are noticing here that the bond-like component got much more valuable. That alone, not the risk component or the growth component, accounts for two decades of huge price rises.

This actually updates significantly some of my own work, and the asset pricing consensus. The great question why do price-dividend ratios vary so much occupied us a lot in the late 1980s and early 1990s, including myself, John Campbell, Bob Shiller, Gene Fama and Ken French. The rough answer we came to -- pretty much all variation in D/P or P/D comes down to variation in risk premiums, the \(r^e=r-r^l\) term. The underlying fact is that times of high P/D are not reliably followed by higher dividend growth (Shiller), and they are reliably followed by low  excess returns (Fama and French). If you add it up, the risk premium effect neatly accounts for all the variation in P/D (Campbell and Shiller, me).

Well, in the data up to 1990, we didn't see much persistent variation in real rates of interest, and what we did see was not correlated well with stock prices. Well, that was 1990, and now is now. This graph suggests that in fact a lot of the recent variation in P/D corresponds to lower real interest rates.  Also, it's the low frequency, decade to decade movement in P/D that is not well accounted for by any models. An academic version of this observation needs to be written.

Practical bottom line: The stories that the recent stock price decline comes from rising long-term real interest rates make sense. They might be wrong, but they make sense. That's saying a lot more than most of the other stories being bandied around right now.

Interest rates, growth,  stock prices, and the Fed. 

The story is not that easy however. We have to think about real interest rates \(r\) and growth \(g\) together. And there is this puzzle to answer -- how can it be that good news about the economy sends the market down? If \(P/D=1/(r-g)\) more \(g\) should raise \(P\), no? It should shift up the dashed line in my first graph?

No. We have to think about where real interest rates come from. One of the most basic relationships in economics is that higher growth means higher real interest rates.  If everyone will be richer in the future -- growth -- they need an incentive to save and not blow it all today. And growth means a higher marginal product of capital, and hence higher interest rates. As a simple equation, \[ \text{real rate} = \gamma g \]where \(\gamma\) is a parameter, usually between about 1/2 and 2, and get ready for a bar fight at the AEA convention over just what value to use. 1% higher growth means about a half percent to two percent higher real interest rate.

(There is a second term too, important in understanding things like the financial crisis. More uncertainty means lower interest rates. Not today.)

If \(\gamma=1\), if one percent growth means one percent higher real interest rates, then higher growth has no effect at all on stock prices or price dividend ratios. (\(D/P = r^l + r^e - g.\) Raise \(r^l\) and \(g\) by the same amount.) If, as I think is more likely right in this case, \(\gamma>1\), then higher growth lowers stock prices. Yes. Higher growth means a higher discount rate as well as more dividends. The discount rate effect can overwhelm the cashflow effect.

This has nothing to do with the Fed. There is a natural human tendency to look for Agency, for some man or woman behind the curtain pulling all the strings, and these days that means the Fed. For example, the WSJ Editorial on stocks:
"The paradox of the equity-market correction is that it’s taking place even as the real economy looks stronger than it’s been since at least 2005 and maybe 1999. "
"So why are stocks falling amid all the good news? The best answer we’ve heard is that stocks are reflecting a return to volatility and risk after years of the Fed’s financial repression. With its quantitative easing bond purchases, the Fed has for a decade suppressed market price signals in bonds."
"Investors may finally be figuring out that the global quantitative-easing monetary party is ending."
Look back at my graph. Real interest rates have been on a slow downward trend since 1980. That trend is unbroken since 2008. There is not a whiff that QE or anything else has budged that trend. (Lots of good graphs on this point in 8 heresies of monetary policy here. ) If the Fed has anything to do with it, it is the slow victory over inflation expectations, not QE and a lot of talk.

Yes, the papers like to say that higher growth will induce the Fed to raise rates. The Fed can put a finger in this dike for a bit if they want to, but even the Fed cannot long fight the positive or negative relationship between real growth and real interest rates.

So it makes perfect sense, at least as a logical possibility, that more growth lowers stock prices! Again, this is like my lower line in the first picture -- and actually a bit better because we also raise the terminal point. If this is what happened, well, regret that you didn't see it happening and stay out during the dip, but be reassured the market will make it back.

Risk premiums 

What about the ``unusually low risk premium''? Aren't the Fed's ``massive QE and abnormally low interest rates distorting risk premiums and causing asset price bubbles?'' (The best definition of ``bubble'' I can muster is a risk premium that is too low, distorted somehow.)

Here is the contrary view. We are at the late summer of the business cycle. The economy is relatively healthy, at least if you're a stock market investor. (Many of these own companies.) Economic volatility is still at an all time low. Bonds are still giving pretty atrocious real returns. Yeah, stocks look pretty healthily priced -- as you contemplate your \(P/D = 1/(r^l + r^e - g)\) it looks like the extra return from stocks \(r^e\) is pretty low. But what else are you going to do with the money? You can afford a little risk. Contrariwise, the same investors in the bottom of the great recession, with very low \( P/D\) signaling a high risk premium \(r^e\), said to themselves or their brokers, yes, this is a buying opportunity, stocks will likely bounce back. But my business is in danger of closing, my house might get foreclosed, I just can't take any risk right now.

In short, it is perfectly rational for investors to be more risk-averse, and demand a higher risk premium \(r^e\) in the bottom of recessions, and to hold stocks despite a low risk premium in quiet good times like right now. And this has nothing to do with the Fed, QE, or anything else.

John Campbell and I wrote a simple model of this phenomenon a long time ago, and I've reviewed it several times since, most recently here. Sorry for flogging the same ideas, but this possibility still hasn't made it to, say, the Fed-obsessed WSJ editorial pages, to say nothing of the Trump-obsessed pages at other outlets.

John and I tied risk aversion to consumption trends. If consumption is high relative to the recent past, in good times, you more willing to hold risk. If consumption is declining relative to the recent past, you get more scared. Lots of other mechanisms, including debt, work much the same way. If you don't like the precise model, consumption relative to recent past is a good general business cycle indicator.

Let's look historically. Here is consumption less a moving average (I used \(x_t = \sum_{j=0}^\infty 0.9^j c_{t-j})\), plotted with the log of the price/dividend ratio. The two series have different scales. The point is to see the correlation.

Consumption minus a moving average, and log P/D on NYSE. 



The pattern is longstanding. In good times, when consumption rises relative to recent past, stock valuations go up. In bad times, such as the great recession, consumption falls and so do stock valuations. People are scared. The same pattern happens regularly in the past.

The two lines drift apart, but as we saw above real interest rates account for that. Then the business-cycle related risk premium here accounts for the rises and dips.

And, if I may belabor the point, there was no QE, zero interest rates, and so forth going on in all these past instances when we see exactly the same pattern. Higher real interest rates are a regular, simple, utterly normal part of expansions, and lower risk premiums are a regular, simple, utterly normal part of expansions. 

I was interested to read Tyler Cowen at Bloomberg back in to this view, based entirely on intuition:
In a volatile and uncertain time politically, we have observed sky-high prices for blue-chip U.S. equities. Other asset prices also seem to be remarkably high: home values and rentals in many of the world’s top-tier cities, negative real rates and sometimes negative nominal rates on the safest government securities, and the formerly skyrocketing and still quite high price of Bitcoin and other crypto-assets.
Might all of those somewhat unusual asset prices be part of a common pattern? Consider that over the past few decades there has been a remarkable increase of wealth in the world, most of all in the emerging economies. Say you hold enough wealth to invest: What are your options?
In relative terms, the high-quality, highly liquid blue-chip assets will become expensive. So we end up with especially high price-to-earnings ratios and consistently negative real yields on safe government securities. Those price patterns don’t have to be bubbles. If this state of affairs persists, with a shortage of safe investment opportunities, those prices can stay high for a long time. They may go up further yet.
These high asset prices do reflect a reality of wealth creation. They are broadly bullish at the global scale, but they don’t have to demonstrate much if any good news about those assets per se. Rather there is an imbalance between world wealth and safe ways of transferring that wealth into the future
To sum this all up in a single nerdy finance sentence, in a world where wealth creation has outraced the evolution of good institutions, the risk premium may be more important than you think.
Except for this business about "shortage of safe assets," that's pretty much the intuition. (Tyler: all assets are in fixed supply in the short run. Prices adjust. This isn't really a ``shortage.'') The point that high valuations extend to homes, bonds, bitcoins, and global stocks is a good indicator that the phenomenon is generalized risk aversion rather than something specific to one market or economy. 

This view should not necessarily make you sleep at night however.  It means that a downturn will be accompanied by higher risk aversion again, and not only will dividends fall, prices will fall further. Moreover, historically, asset price falls have been preceded by periods of higher volatility. Alas, many periods of higher volatility have just faded away, so it's a warning sign not a signal.  Sure, this mechanism means they will bounce back, but if you are clairvoyant enough to see it coming it will be better to avoid the fall! If not, well, be read to buy when everyone else is scared -- if you are one of the lucky few who can afford not to be scared.

The VIX, volatility, technical factors 

There is another kind of ``discount factor variation,'' including 1987 and the flash crash. Sometimes the machinery of markets gets in the way, and prices fall more than they should. They quickly bounce back. If you can buy at the bottom you can make a fortune, but the prices fell precisely because it's hard to buy.

There were scattered report on Monday of hours long delays for retail customers to trade. (Can't find link.) But I do not get a sense this was a big clog in the markets. I would be curious to hear from people closer to markets.

The bigger news is the return of volatility -- big daily changes. To put this in historical perspective, here are two plots




The surprise, really, is just how low low volatility had become. Historically the stock market index has had a volatility around 15-20% per year -- a typical year saw a 15-20% change, and a typical day saw a \(15-20 / \sqrt{250} \approx \) one percent change. But, as you see in the top graph, volatility also declines in the late summer of the business cycle. Volatility has many occasional little eruptions, typically around price drops, and then washes away. Except when volatility rises in advance of the next recession and market decline. Which is this? I wish I knew.

Volatility is not about "fear" nor is it about "uncertainty." Volatility occurs when options change quickly. Constant bad news or good news just leads to constantly low or high prices. This is a sign of a time when either a lot of real information is hitting the market, or a lot of people are trying to process what's going on ahead of everyone else.

The "VIX bust" is hot in the news. A lot of people bet that the graph you saw above would not rise. To be ``short volatility'' means basically that you write insurance to people who worry about markets going down, (volatility is a big part of the value of put options) and you write insurance to people who are worried about events like right now in which markets start to move a lot. Hello, when you write insurance, occasionally you have to pay up.

As the graphs make clear, writing volatility insurance, or betting that volatility will continue to go down,  is like writing earthquake insurance. Not much happens for many years in a row, and you can post nice profits. Then it jumps and you lose big time. Anyone who did this based just on historical returns is now crying the tears of the greedy neophyte. But they have lots of company. Back in the 1990s, Long Term Capital Management went under, basically for betting that similar looking graphs would continue to go down.

Well, if after all these years people are at it, P.T. Barnum had a good word for them. But did this have something to do with the stock market crash? How Bets Against Volatility Fed the Stock Market Rout in WSJ is an example of this train of thought.

On first glance, sure, a lot of people lost a ton of money, and then sold out other risky positions. But Econ 101: for every buyer there is a seller.  Derivatives contracts are pure cases of this fact -- the net supply really is zero, for everybody who lost a dollar shorting VIX somebody else made a dollar buying it.

To get a story like this to go you need all sorts of market discombobulations. Somehow the people who lost money must be more important to markets than the people who made money. This can happen -- if a bunch of traders in a complex obscure security all lose money, and all try to sell, there is nobody to buy. But I don't really see that case here, and stocks are not a complex obscure security.

A trader friend also tells me that he has seen lots of people stop hedging -- so sure low volatility would continue that they don't cover the downside. He said many have lost a ton, and now are frantically selling to cover their positions. Such price pressure can have short run impacts, but does not last long.

Inflation and real interest rates 

So we're back at hints of higher long-term real interest rates as the main likely culprit behind this week's decline and gyrations.

Here too most of the stories don't make much sense. Inflation per se should not make much difference. If expected inflation rises, interest rates rise, but real interest rates are unaffected. Inflation may make the Fed act more quickly, but there is not much correlation between what the Fed does with short term rates and the behavior of 10 year or more rates that matter to the stock market -- or to corporate investment.



Yes, there is some correlation -- especially at the end of expansions, short and long rates rise together. But the correlation is a whole lot less than the usual Wizard of Oz behind the curtain stories. And even the Fed cannot move real rates for very long. There is a good chicken-and-egg question whether the Fed can hold short rates down for long when long rates want to rise. The Fed pretty much has to jump in front of the parade and pretend to lead it.

Inflation does seem finally to be rising. The fact that higher rates are associated with the dollar falling suggests that a lot of the higher rates are due to inflation, and TIPs have not moved (top graph.)

So, the question before us is, are long-term real rates finally rising -- back to something like the historical norm that held for centuries, and if so why?

The good story is that we are entering a period of higher growth. Depending on your partisan tastes, point to tax cuts and deregulation, or state that Obama medicine is finally kicking in. This would raise real growth, with \(\gamma>1\) lead to a small stock price decline, but higher stock returns and bond returns going forward.

There is a bad story too. Having passed a tax cut that left untouched will lead to trillion-dollar deficits, Congressional leaders just agreed to $300 billion more spending. The Ryan plan that tax cuts would be followed by entitlement reform may be evaporating. Publicly held debt is $20 trillion. At some point bond markets say no, and real rates go up because the risk premium goes up. The US is in danger that higher interest rates mean higher interest costs on that debt, which means higher deficits, which means higher interest rates. $20 trillion times 5% interest = $1 trillion in interest costs.

The former leads to some inflation if you believe in the Phillips curve. The latter leads to stagflation in a tight fiscal moment.

Which is it? I don't know, I'm an academic not a trader.

One consolation of the stock market decline: I hope we don't have to hear how all the corporate tax cut did was to boost the stock market!

Well, two days ago this was going to be a short post responding to the WSJ's view that the Fed is behind it all, and Tyler's nice intuition. It got a bit out of hand, but I hope it's still interesting.


****

Data Update (Geeks only).

P/D isn't really "better" than P/E or other measures. A measure is what it is, you have to specify a question before there is an answer. Ideally, we want a measure that isolates expected returns, and tells us if prices are higher or lower given the level of expected dividends.  So ideally, we would account for expected future dividends and the result would be a pure measure of expected returns (rational or not). P/D works pretty well that way because dividends are not very forecastable. Price divided by this year's dividends turns out to be a decent approximation to price divided by anyone's forecast of future dividends. But not perfect. P/E is less good that way because earnings bat about a bit more than dividends. For individual companies you can't use P/D, because so many of them do not pay dividends. Following Fama and French, the ratio of market value to book value is better there, because book value is usually positive, or not so frequently zero.

I use the CRSP definitions. I start from the CRSP return with and without dividends and infer the dividend yield. ''Dividends" here includes not only cash dividends but all cash payments to shareholders. So, if your small company gets bought by Google, and the shareholders get cash, that is a "dividend" payout. I suspect this accounts for the difference noted by WC Varones below. As others point out, earnings has all sorts of measurement issues, and also does not control for leverage.

Dividends are very seasonal, so you can't divide price by this month's dividends or you get a lot of noise. I use the last year's worth of dividends, brought forward by reinvesting them. This introduces some "return" into the dividend series. If you just sum dividends, though, identities like \(R_{t+1} = (P_{t+1}+D_{t+1})/P_t \) no longer hold in your annual data.

x = load('crsp_nyse_new_2018.txt');

caldt = x(:,1);
totval = x(:,2);
usdval  = x(:,3);
sprtrn = x(:,4);
spindx = x(:,5);
vwretd = x(:,6);
vwretx = x(:,7);

[yr,mo,day,crsp_date_number] = decode_date(caldt);

T = size(vwretd,1);
vwretda = (1+vwretd(1:T-11)).*(1+vwretd(2:T-10)).*(1+vwretd(3:T-9)).*...
          (1+vwretd(4:T-8)).*(1+vwretd(5:T-7)).*(1+vwretd(6:T-6)).*...
          (1+vwretd(7:T-5)).*(1+vwretd(8:T-4)).*(1+vwretd(9:T-3)).*...
          (1+vwretd(10:T-2)).*(1+vwretd(11:T-1)).*(1+vwretd(12:T));

vwretxa = (1+vwretx(1:T-11)).*(1+vwretx(2:T-10)).*(1+vwretx(3:T-9)).*...
          (1+vwretx(4:T-8)).*(1+vwretx(5:T-7)).*(1+vwretx(6:T-6)).*...
          (1+vwretx(7:T-5)).*(1+vwretx(8:T-4)).*(1+vwretx(9:T-3)).*...
          (1+vwretx(10:T-2)).*(1+vwretx(11:T-1)).*(1+vwretx(12:T));
   
vwdp = vwretda./vwretxa-1; %D_t+1/P_t+1 = [(P_t+1+D_t+1)/P_t] / [P_t+1/P_t] -1;
vwdda = vwdp(13:end)./vwdp(1:end-12).*vwretxa(13:end);   % D_t+1/D_t = D_t+1/P_t+1 / D_t/P_t * P_t+1/P_t
vwdda = [ones(23,1)*NaN; vwdda];
cumval = cumprod(1+vwretd);
vwdp = [ ones(11,1)*NaN; vwdp]; % keep length of series the same

I get stock data from CRSP via WRDS. This is the NYSE only. I can't post the full data, as it belongs to CRSP. Here is an excerpt that will let you calculate the last year, and check that things are right if you download the whole thing.

%crsp_nyse_new_2018.txt
%   caldt            totval                  usdval                 sprtrn         spindx        vwretd        vwretx
19260130       27624240.80       27412916.20      0.022472       12.74      0.000561     -0.001395
19260227       26752064.10       27600952.10     -0.043956       12.18     -0.033046     -0.036587
19260331       25083173.40       26683758.10     -0.059113       11.46     -0.064002     -0.070021
19260430       25886743.80       24899755.60      0.022688       11.72      0.037019      0.034031
...
20160129    17059005700.00    17976992500.00     -0.050735     1940.24     -0.050111     -0.051700
20160229    16986848800.00    17001893900.00     -0.004128     1932.23      0.005104      0.002251
20160331    18122913200.00    16951468600.00      0.065991     2059.74      0.072190      0.069562
20160429    18503144900.00    18082712100.00      0.002699     2065.30      0.023324      0.021716
20160531    18479138100.00    18410229900.00      0.015329     2096.96      0.006124      0.003392
20160630    18613173100.00    18422135300.00      0.000906     2098.86      0.011175      0.008957
20160729    19054705700.00    18557630600.00      0.035610     2173.60      0.028433      0.026872
20160831    18993464300.00    19049575300.00     -0.001219     2170.95      0.000196     -0.002532
20160930    18829544800.00    18880924600.00     -0.001234     2168.27     -0.003876     -0.005878
20161031    18404742600.00    18802632900.00     -0.019426     2126.15     -0.021331     -0.022944
20161130    19220882900.00    18383296300.00      0.034174     2198.81      0.048548      0.045701
20161230    19568491300.00    19178151000.00      0.018201     2238.83      0.021566      0.019486
20170131    19824534000.00    19526674900.00      0.017884     2278.87      0.014007      0.012623
20170228    20355248600.00    19781803200.00      0.037198     2363.64      0.031422      0.028905
20170331    20237616500.00    20334429600.00     -0.000389     2362.72     -0.003961     -0.006103
20170428    20286715000.00    20194157100.00      0.009091     2384.20      0.003950      0.002468
20170531    20299003900.00    20276905500.00      0.011576     2411.80      0.002199     -0.000507
20170630    20602218600.00    20256933000.00      0.004814     2423.41      0.018204      0.016235
20170731    20747539100.00    20488018000.00      0.019349     2470.30      0.015290      0.013394
20170831    20593088100.00    20742392900.00      0.000546     2471.65     -0.005133     -0.007874
20170929    21147810200.00    20381001300.00      0.019303     2519.36      0.030435      0.028662
20171031    21343546700.00    21130998500.00      0.022188     2575.26      0.011831      0.010360
20171130    21904734200.00    21302790800.00      0.028083     2647.58      0.030537      0.027670
20171229    22016063100.00    21683038400.00      0.009832     2673.61      0.015914      0.014117



If I screwed up, let me know and I'll fix it!





Asset Pricing Competition


John Campbell's text, "Financial Decisions and Markets" is out from Princeton University Press. With some mild chagrin, I must say it's a splendid book. (Chagrin, of course, because it's an obvious major competitor to my own effort in Asset Pricing.)

It is spare, concise, and clearly written. How can I say that of a 450 page book, with wide text and tiny margins? Well, it's the concise version of the Encyclopedia Britannica, breathtakingly comprehensive and up to date in its coverage of important research topics.

The first part is a whirlwind tour of asset pricing theory. Here, John adopts the traditional organization -- expected utility, static portfolio choice, static CAPM and APT as equilibrium relations where supply meets demand, and finally we meet the discount factor and consumption-based pricing. I chose to go the other way around, and start with the basic asset pricing equation \(p_t u'(c_t) = E_t [\beta u'(c_{t+1}) x_{t+1} ]\), following Bob Lucas' insight that asset pricing is the same as in an endowment economy, and filling out the CAPM and APT and so forth as special cases. I never even got to portfolio theory -- it's in a draft chapter for the long-delayed next version. I still think that's the right organization, but most people don't want to teach it that way. John's more conventional organization, combined with clarity and concision, may be more what you want.

Even here, John's empirical taste and contributions rings through Any textbook is in many ways a summary of its authors' research journey, and John's journey has gone far and wide. You see a preview of the style on the 6th page of chapter 2 (p. 28) where you meet approximations for log returns, and the growth-optimal portfolio on the next page. On calculating minimum-variance portfolios, on p. 37, you get  graph of time-varying return correlations from Campbell Lettau Milkier and Xu (2001), a provocative fact usually ignored. After efficiently presenting the classic CAPM, we get (p. 51) an insightful application to Harvard's endowment, highlighting the difficulties of using these oft-repeated portfolio and pricing theories in practice.
This book is  infused with up to the minute empirical work and practical application even in the most basic theory sections. Starting on p. 61 John moves swiftly from the CAPM theory to empirical evidence, and implicitly, methodology. The next 16 pages cover the standard regression test approaches, swiftly show the evidence for the value and size cross sections, a nice treatment of momentum, a good yet economical coverage of the major anomalies and then a quick and digestible survey of reactions such as conditional capm, multifactor models, and behavioral finance. The coverage is comprehensive and up to date without being overwhelming.

Then the book really gets going. You would expect Chapter 5 on present value models to be excellent, and it is, somehow while also being brief. It covers not just the basics such as Campbell Shiller present value model and VARs, but includes a useful section on "Interpreting US stock market history" to bring equations alive, an excellent section on the econometrics of return forecasting, drifting steady state models, present value models in the cross section and more. Somehow in 40 pages John has distilled his own major research contributions, and several hundred papers of a still active literature, yet brought you up to date. My coverage focused only on the simplest idea, and wasn't one tenth this complete a summary of the current literature.

Chapter 6 on consumption based asset pricing is likewise elegant and comprehensive. John jumps right in to data with the equity premium, riskfree rate, and volatility puzzles (p. 164). Then he quickly outlines the huge literature of responses to the puzzles (p. 167) again in short digestible paragraphs. The big ones, time varying disasters, Epstein-Zin, long-run risk, ambiguity aversion and (nearly last but not least) habit formation and durable goods each get a few well-chosen pages, each self contained with derivations (a derivation of the Epstin-Zin SDF is not fun), but not windy. Unusually, John also includes an elegant chapter 7 on production-based asset pricing and general equilibrium. I think this approach is relatively unexplored and promising -- I'm glad to infer John agrees. In both areas, my latest survey in Macro-Finance is not nearly as economical. John spryly gets to the point.

It wold not be a John Campbell book without a chapter on fixed income, and this one does not disappoint. Affine models, empirical work on the expectations hypothesis, a strong emphasis on the link between macroeconomics and term structure - absent in most treatments -- and linking interest rates and exchange rates are strong points.

Here though, you see one limitation of the book, in scope at least. Everything, including fixed income, is done in discrete time. This fact certainly makes it more accessible to economists, and most of John's voluminous work has been in discrete time. But most of the ideas in asset pricing are much easier in continuous time, once one masters the elements of Ito's lemma manipulations.  Term structure models are commonly done in continuous time. In revising Asset Pricing and the online versions, I have moved entirely to continuous time rather than lognormal approximations. It's much simpler that way, and continuous time is a standard part of a finance PhD's toolkit. This otherwise comprehensive book doesn't have any option pricing in it, though Black-Scholes is a cornerstone of finance. Well, John hasn't worked on that, and his research is mostly presented in discrete time. Adding continuous time would add a lot of pages. It keeps the book quite self contained. But it does mean that a course in finance will need some other reference material for that important part.

The next three chapters reflect again many of John's wide-ranging contributions.  It is a crime that we still use static mean-variance optimization -- and by "we" I include the entire industry as well as academia -- when we know state variables are moving around all the time. John has made some great strides in trying to make intertemporal portfolio allocation and inter temporal asset pricing come alive. There is a lot left to do here, but if you want to get started Chapter 9 on inter temporal risk brings you up to date (or at least faster than trying to read all of John's papers!)

Chapter 10 on household finance is a great example of a topic that is new to the asset pricing canon. How do we understand what portfolios people actually hold?  You get a great summary of that work. It's followed by an excellent Chapter 11 on the economics of risk sharing and speculation and Chapter 12 on asymmetric information and liquidity. This too is not yet part of the textbook canon but soon will be, as these issues are central to current research.  The classic theory of finance, the joke goes, is perfectly mirrored in the market for senior faculty: Prices change, there is no volume. There is a recent explosion in understanding the mechanics of trading, and these spare chapters will send students on their way.

Like continuous time, the book also does not have a chapter on the recent explosion of models in asset pricing with financial frictions. Perhaps John just hasn't written in that area yet! But an author (me) whose finance book omitted a chapter on portfolio theory can hardly complain, and knowing John's evident mania for scholarship, it will likely be there in the revision.

In sum, this is a must-read book for any Ph. D. student in finance or financial economics, and must-have book for any serious scholar of finance. It is not organized, as I tried to do in Asset Pricing around a Big Idea, trying to move how we do research in a particular direction. That is likely an advantage. Instead, it shines in a crystal-clear, nearly encyclopedic summary of current ideas in the macroeconomics and finance literature, complete with an equally encyclopedic citation list for those wanting to go further. It is distilled like fine scotch. Barrels of fine scotch.

Bitcoin and Bubbles

Source: Wall Street Journal

So, what's up with Bitcoin? Is it a "bubble?'' A mania of irrational crowds?

It strikes me as a fairly pure instance of a regularly occurring phenomenon in financial markets, one that encompasses some "excess valuations" in stock markets, gold and commodities, and money itself.

Let's put the pieces together. The first equation of asset pricing is that price = expected present value of dividends. Bitcoin has no cash dividends, and never will. So right off the bat we have a problem -- and a case that suggests how other assets might have value above and beyond their cash dividends.

Well, if the price is greater than zero, either people see some "dividend," some value in holding the asset, beyond its cash payments; equivalently they are willing to hold the asset despite a lower expected return going forward, or they think the price will keep going up forever, so that price appreciation alone provides a competitive return. The first two are called "convenience yield," the latter is a "rational bubble."

"Rational bubbles" are intriguing, but I think fundamentally flawed. If a price goes up forever, eventually the value of bitcoin must exceed all of US wealth, then all of world wealth, then all of interplanetary wealth, then all of the atoms in the universe. The "greater fool" or Ponzi scheme theory must break down at some point, or rely on an irrational belief in the next fool. The rational bubbles theory also does not account for the association of price surges with high volatility and high trading volume.

So, let's think about "convenience yield." Why might someone be willing to hold bitcoins even though their price is above "fundamental value" -- equivalently even though their expected return over a decently long horizon is lower than that of stocks and bonds? Even though we know pretty much for sure that within our lifetimes bitcoin will become worthless? (If you're not sure on that, more later)


Well, dollar bills have the same feature. They don't pay interest, and they don't pay dividends. By holding dollar bills, you are holding an asset whose fundamental value is zero, and whose expected return is demonstrably lower than that of, say, one-year treasuries. One year Treasuries are completely risk free, and over a year will give you about 1.5% more than holding dollar bills. This is a pure arbitrage opportunity, which isn't supposed to happen in financial markets!

It's pretty clear why you still hold some dollar bills, or their equivalent in non-interest-bearing accounts. They are more convenient when you want to buy things. Dollar bills have an obvious "convenience yield" that makes up for the 1.5% loss in financial rate of return.

Also, nobody holds dollar bills for a whole year. You minimize the use of dollar bills by going to fill up at the ATM occasionally. And the higher interest rates are, the less cash you hold and the more frequently you go to the ATM. So, already we have an "overpricing" -- dollars are 1.5% higher priced than treasurys -- that is related to "short-term investors" and lots of trading -- high turnover, with more overpricing when there is more trading and higher turnover -- just like bitcoin. And 1999 tech stocks. And tulip bubbles.

Some of the convenience yield of cash is that it facilitates tax evasion, and allows for illegal voluntary transactions such as drugs and bribes. We can debate if that's good or bad. Lots of economists want to ban cash (and bitcoin) to allow the government more leverage. I'm less enthusiastic about suddenly putting out of work 11 million undocumented immigrants and about half of small businesses. The US tends to pass a lot of aspirational laws that if enforced would bring the economy to a halt. To say nothing of the civil liberties implications if the government can track every cent everyone has ever spent.

But US cash is largely stuffed in Russian mattresses. It is even less obvious that it is in our interest to enforce Russian laws on taxation or Russian control over transactions. Or Chinese, Venezuelan, Cuban, etc. control.

And more so bitcoin. This is the obvious "convenience yield" of bitcoin -- the obvious reason some people are willing to hold bitcoin for some amount of time, even though they may know it's a terrible long-term investment. It certainly facilitates ransomware. It's great for laundering money. And it's great for avoiding capital controls -- getting money out of China, say. As with dollars there is a lot of bad in that, and a lot of good as well. (See Tyler Cowen on some parallel benefits of offshore investing.)

But good or bad is beside the point here. The point here is that there is a perfectly rational demand for bitcoin as it is an excellent way to avoid both the beneficial and destructive attempts of governments to control economic activity and to grab wealth -- even if people holding it know that it's a terrible long-term investment.

On top of this "fundamental" demand, we can add a "speculative" demand. Suppose you know or you think you know that bitcoin will go up some more before its inevitable crash. In order to speculate on bitcoin, you have to buy some bitcoin. I don't know if you can short bitcoin, but if you wanted to you would have to borrow some bitcoin and sell it, and in the process you would have to hold some bitcoin. So, as we also see in high-priced stocks, houses and tulips, high prices come with volatile prices (so there is money to be made on speculation), and large trading volumes. Someone speculating on bitcoin over a week cares little about its fundamental value. Even if you told him or her that bitcoin would crash to zero for sure in three years, that would make essentially no dent in their trading profits, as you can make so much money in a volatile market over a week, if you get on the right side of volatility.

Now to support a high price, you need restricted supply as well as demand. There are only so many bitcoins, as there are only so many gold bars, at least for now.  But that will change. The Achilles' heel of bitcoin's long term value is that there is nothing to stop people from creating bitcoin substitutes -- there are already hundreds of other similar competitors. And there is nothing to stop people from creating private claims to bitcoin -- bitcoin futures -- to satisfy speculative demand. But all that takes time. And none of my demands were from people who want to hold bitcoin for very long.  Ice cream is also a fast-depreciating asset, but people hold it for a while. In this view, however, Bitcoin remains a terrible buy-and-hold asset, especially for an investor who plans to pay taxes.

In sum, what's going on with Bitcoin seems to me like a perfectly "normal" phenomenon. Intersect a convenience yield and speculative demand with a temporarily limited supply, plus temporarily limited supply of substitutes, and limits on short-selling, and you get a price surge. It helps if there is a lot of asymmetric information or opinion to spur trading, and given the shady source of bitcoin demand -- no annual reports on how much the Russian mafia wants to move offshore next week -- that's plausible too.

This view says that price surges only happen with restricted supply, and accompany price volatility, large trading volume, and short holding periods. That's a nice testable link, which seems to hold for bitcoin. And other theories, such as madness of crowds, no not explain that correlation.

Bitcoin is not a very good money. It is a pure fiat money (no backing), whose value comes from limited supply plus these demands. As such it has the huge price fluctuations we see. It's an electronic version of gold, and the price variation should be a warning to economists who long for a return to  gold. My bet is that stable-value cryptocurrencies, offering one dollar per currency unit and low transactions costs, will prosper in the role of money. At least until there is a big inflation or sovereign debt crisis and a stable-value cryptocurrency not linked to government debt emerges.

(This view is set out in more detain in a paper I wrote about the tech stock era,  Stocks as Money in William C. Hunter, George G. Kaufman and Michael Pomerleano, Eds., Asset Price Bubbles Cambridge: MIT Press 2003. Alas not available online, but the link to my last manuscript works.)

Update: Marginal Revolution also on bitcoin today.

Online Asset Pricing is back!

The online Asset Pricing Ph.D. class is back! It died in a Coursera "upgrade," but it is now migrated over to Canvas.

Click here to go to the online class. My Asset Pricing webpage has links to the class, book, and many other useful materials.

It should be open and free to anyone, including all the quizzes, problem sets and exams.

Since it's on the Canvas system, if you are teaching at a University that uses Canvas, you should be able to integrate it with your class, assign all or part of it, and receive grades from quizzes and problem sets. Thus, you can use it as a flipped classroom, assign selected videos and quizzes in advance of a lecture.

It is also ideal for a Ph. D.  program summer school for year 0 or year 1. Again, through Canvas you should be able to assign the class, in whole or in part, and get grades.

It's also well suited to self-study. If you just want to watch the videos and read the notes, they are all here via youtube links on the Asset Pricing webpage.

Huge thanks to Emily Bembeneck and Allison Kallo at the University of Chicago, Mikhail Proshletsov, and above all to Nina Karnaukh now at Ohio State. Nina masterminded all the hard work of moving the class pages and quizzes from the Coursera system to the Canvas system, and fixing innumerable glitches along the way. Thanks also to the Booth School for paying for the transition.