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A Generous Fed Isn’t Really the Good News it Sounds Like

October 31, 2019 10 comments

I understand why people are delighted about Powell’s remarks yesterday, about how the Fed would need to see a significant and sustained increase in inflation before hiking rates again. This generation, and the last, does not see inflation as a significant threat, nor a significant cost should it get going, and believes firmly that the Fed can easily squelch it if it gets going. (They believe this because, after all, the Fed told them so).

Older investors might be more reticent to believe that there’s a pony in there somewhere, since the evidence suggests that not only does inflation erode purchasing power (thereby demanding even more nominal return be provided by portfolios that are already overstretched valuation-wise) but it also ruins the diversification effect of bonds relative to stocks. The main reason that 60:40 is a dramatically lower risk portfolio (and more efficient in an investing sense) than 100% stocks is that stock and bond returns have tended to be inversely correlated for a long time. When stocks go up, bonds go down, in general (and vice-versa). But that’s because they have inverse sensitivities to the economic growth factor. In recent years, that has been the only factor that matters, but stocks and bonds have the same sensitivity to the inflation factor: when inflation goes up, both stocks and bonds tend to decline (and vice-versa). Consequently, when inflation becomes an important element in investors’ calculations the correlation of stocks and bonds tends to be positive and in the immortal words of Billy Joel in “Goodnight Saigon,” “We would all go down together.” Along these lines I recently prepared this chart for Real Asset Strategies,[1] illustrating that when inflation is over about 2.5%, correlations tend to flip. This is a 3-year average of y/y inflation (and shown on the chart as inflation minus 2.5% so the zero line is what matters, not the line at 2.5%) versus 3-year correlations; the point is that you don’t need 4% inflation to drastically change the value of the 60:40 portfolio.

I also think that people give the Fed much more credit for their ability to squelch inflation – which after all they haven’t had to do for more than 30 years after spending 15 years squelching the last round – than they deserve. But that’s a ‘show me’ situation and it’s hard to prove my suspicion that they won’t be so successful when push comes to shove.

So, I understand why people are partying about a Fed that is even looser than it had been. I don’t think that’s the correct response, but I understand it.

I also understand why people are somewhat morose about trade frictions. It isn’t for the right reason, that in the long run it will hurt real growth a smidge and increase inflation a smidge-and-a-half, but because they think it will have a drastic effect on near-term growth. That’s why everyone gets so excited about any inkling the US and China are nearing a trade détente and so depressed when it looks like they aren’t. We are told that the current global slowdown is being caused largely by the trade war.

In my view that’s nonsense. The global economy has been expanding for a decade on exceptionally loose liquidity but no tree grows to the sky. The global economy was slowing well before the trade frictions could possibly have had any impact. But it is hard to convince people of that, because everyone knows that:

GDP = C + I + G + (X-M),

or consumption plus investment plus government spending plus trade. And we learned in school about Ricardian comparative advantage and how trade enriches (or anyway, can enrich) both parties at the same time. So if China doesn’t import anything from the US and doesn’t export anything to the US, growth is going to be crushed, right?

But that’s not how trade works. Frankly, that’s not how anything in the GDP equation works. If you remove the final term, you don’t reduce GDP by (X-M). Sure, if this was an algebra problem you would, but it’s not. In the real world, what you lose from trade gets partially replaced by an increase in consumption, investment, or government. Just as I pointed out last year with soybeans, if China buys zero from us it means they have to buy them from someone else, which means that supplier doesn’t have them to sell to one of their traditional customers…who then buys them from us. Incidentally, neither beans nor corn went to zero after mid-2018 (see chart, source Bloomberg, normalized to December 2017=100).

The rest of trade works the same way if the two parties are “internal customers” and “external customers.” Though there will always be winners and losers, if we don’t have international trade then we won’t have a destination for our merchandise overseas…but we will also have consumers who don’t have Chinese goods to buy and so need to buy something from a domestic producer instead. This is not a zero sum game; it clearly results in a loss for all players. But the order of magnitude of this loss in the short run is not very big at all, especially for a country with a large fraction of its domestic production going to domestic consumption, as in the US but not even for the world at large. The world economy has lots of reasons to slow and go into recession, and trade frictions are one of those reasons, but certainly not the only one and not even the largest reason.

An overreaction by markets to anything in a stream of economic news is not unique or new, of course; those overreactions won Robert Shiller a Nobel Prize after all for his work pointing out the “excess volatility puzzle” as an early highlight of the nascent field of behavioral economics. But there’s a good reason to ignore most of these wiggles and focus on the long-term effect of these developments. Which, in the case of both the general climate of trade and the Fed’s reaction function to inflation, are negatives for both stocks and bonds.


[1] As part of Enduring Intellectual Properties’ investment in Real Asset Strategies, I serve as Director of Research for the firm. Real Asset Strategies LLC offers liquid real asset strategies focused on diversification benefits and inflation protection at reasonable fees.

The Fed’s Reserves Management Problem

October 22, 2019 Leave a comment

There has been a lot written about the Fed’s recent decision to start purchasing T-bills to re-expand its balance sheet, in order to release some of the upward pressure on short-term interest rates in the repo market. Some people have called this a resumption of Quantitative Easing, while others point out that it is merely an adjustment to a technical condition of reserves shortage. The problem is that both perspectives may be right, under different circumstances, and that is the underlying problem.

The triggering issue here was that overnight repo rates had been trading tight, and in fact briefly spiked to around 10%. It isn’t surprising that the Federal Reserve responded to this problem by adding lots of short-term liquidity: that’s how they respond to every issue. Banks in trouble? Add liquidity. Economy slightly weak? Add liquidity. “Stranger Things” episode somewhat disappointing? Add liquidity.

Traditionally, the Fed’s response would have been correct. In the “old days,” the overnight interest rate was how the Open Markets Desk gauged liquidity in the interbank market. If fed funds were trading above the Fed’s desired target (which was not always announced, but which could always be inferred by the Desk’s actions in response to reserves tightness or looseness), the Fed would come in to do “system” repos and add short-term liquidity. If fed funds were trading below the target, then “matched sales” was the prescription. It was fairly straightforward, because the demand for reserves was relatively easy to monitor and the adjustments to the supply of reserves small and regular.

But the problem today goes back to something I wrote about back in March, and that’s that reserves no longer serve just one function. In those aforementioned “old days,” the function of reserves was to support a bank’s lending activities in a straightforward statutory formula that was easy for a bank to calculate: this amount of lending required that amount of reserves, calculated over a two-week period ending on a Wednesday. Under that sort of regime, spikes in funds and repo rates (other than occasionally over the turn of year-end) were very rare and the Desk could easily manage them.

This is no longer the case. Reserves now serve two functions, as both lending support and as “High Quality Liquid Assets” (HQLA) that systemically-important banks can use in calculating its Liquidity Coverage Ratio (LCR). This has two really critical implications that we will only gradually learn the importance of. The first implication is that, because the amount of reserves needed to support lending activities is unlikely to be exactly the amount of reserves needed for a bank to achieve its HQLA, at any given time one of these two effects will dictate the amount of reserves the system needs. For example if banks need more reserves for HQLA reasons, then it means they will have more reserves than needed for their existing loan books – and that means economic stability and inflation control will in those cases take a back seat to bank stability. So, as the Fed has struggled to keep up with HQLA demand, year-over-year M2 growth (which is partly driven by reserves scarcity or plenty) has risen fairly quickly to 2-year highs (see chart, source Bloomberg).

The second implication is that, because the demand for each of these two functions of reserves changes independently in response to changes in interest rates and other market forces, it is not entirely knowable or forecastable by the Desk how many reserves are actually needed…and that number could change a lot. For example, there are other assets that also serve as HQLA; so if, for example, T-bill yields were a bit higher than the interest paid on reserves a bank might choose to hold more Tbills and only as much reserves as needed to support its lending activities. But if Tbill rates then fall, or customers lift those bills away from the bank’s balance sheet, or the denominator of the LCR (the riskiness of the bank’s activities, essentially) changes due to market conditions, the bank may suddenly choose to hold lots more reserves. And so rates might suddenly spike or plummet for reasons that have to do with the demand and supply of reserves for the HQLA function, with the Fed struggling to add or subtract large amounts of reserves over short periods of time.

In such a case, targeting a short-term interest rate as a policy variable is going to be exquisitely more difficult than it used to be, and honestly it isn’t clear to me that this is a solvable problem under the current framework. Either you need to declare that reserves don’t qualify as HQLA (which seems odd), or you need to require that a bank hold a certain amount as HQLA and set that number high enough that reserves are essentially the only HQLA a bank has (which seems punitive), or you need to accept that the central bank is either going to have to surrender control of the money supply (which is scary) or of short-term interest rates (which is also scary).

But simply growing the balance sheet? That’s the right answer today, but it might be the wrong answer tomorrow. It does, though, betray that the central bank has a knee-jerk response to err on the side of too much liquidity…and those of us who remember that inflation is actually a real thing see that as a reason for concern. (To be fair, central banks have been erring on the side of too much liquidity for quite some time. But maybe they’ll keep being lucky!)

How Not to Do Income-Disparity Statistics

June 10, 2019 4 comments

I am a statistics snob. It unfortunately means that I end up sounding like a cynic most of the time, because I am naturally skeptical about every statistic I hear. One gets used to the fact that most stats you see are poorly measured, poorly presented, poorly collected, or poorly contexted. I actually play a game with my kids (because I want them to be shunned as sad, cynical people as well) that I call “what could be wrong with that statistic.” In this game, they have to come up with reasons that the claimed implication of some statistic is misleading because of some detail that the person showing the chart hasn’t mentioned (not necessarily nefariously; most users of statistics simply don’t understand).

But mostly, bad statistics are harmless. I have it on good authority that 85% of all statistics are made up, including that one, and another 12.223% are presented with false precision, including that one. As a result, the only statistic that anyone believes completely is the one they are citing themselves. So, normally, I just roll my eyes and move on.

Some statistics, though, because they are widely distributed or widely re-distributed and have dramatic implications and are associated with a draconian prescription for action, deserve special scrutiny. I saw one of these recently, and it is reproduced below (original source is Ray Dalio, who really ought to know better, although I got it from John Mauldin’s Thoughts from the Frontline).

Now, Mr. Dalio is not the first person to lament how the rich are getting richer and the poor are getting poorer, or some version of the socialist lament. Thomas Piketty wrote an entire book based on bad statistics and baseless assertions, after all. I don’t have time to tackle an entire book, and anyway such a work automatically attracts its own swarm of critics. But Mr. Dalio is widely respected/feared, and as such a simple chart from him carries the anti-capitalist message a lot further.[1]

I quickly identified at least four problems with this chart. One of them is just persnickety: the axis obviously should be in log scale, since we care about the percentage deviation and not the dollar deviation. But that is relatively minor. Here are three others:

  1. I suspect that over the time frame covered by this chart, the average age of the people in the top group has increased relative to the average age of the people in the bottom group. In any income distribution, the top end tends to be more populated with older people than the bottom end, since younger people tend to start out being lower-paid. Ergo, the bottom rung consists of both young people, and of older people who haven’t advanced, while the top rung is mostly older people who have Since society as a whole is older now than it was in the 1970s, it is likely that the average age of the top earners has risen by more than the average age of the bottom earners. But that means the comparison has changed since the people at the top now have more time to earn, relative to the bottom rung, than they did before. Dalio lessens this effect a little bit by choosing 35-to-64-year-olds, so new graduates are not in the mix, but the point is valid.
  2. If your point is that the super-wealthy are even more super-wealthier than they were before, that the CEO makes a bigger multiple of the line worker’s salary than before, then the 40th percentile versus 60th percentile would be a bad way to measure it. So I assume that is not Dalio’s point but rather than there is generally greater dispersion to real earnings than there was before. If that is the argument, then you don’t really want the 40th versus the 60th percentile either. You want the bottom 40% versus the top 40 percent except for the top 1%. That’s because the bottom of the distribution is bounded by zero (actually by something above zero since this chart only shows “earners”) and the top of the chart has no bound. As a result, the upper end can be significantly impacted by the length of the upper tail. So if the top 1%, which used to be centi-millionaires, are now centi-billionaires, that will make the entire top 40% line move higher…which isn’t fair if the argument is that the top group (but not the tippy-top group, which we all agree are in a category by themselves) is improving its lot more than the bottom group. As with point 1., this will tend to exaggerate the spread. I don’t know how much, but I know the direction.
  3. This one is the most insidious because it will occur to almost nobody except for an inflation geek. The chart shows “real household income,” which is nominal income (in current dollars) deflated by a price index (presumably CPI). Here is the issue: is it fair to use the same price index to deflate the incomes of the top 40% as we use to deflate the income of the bottom 40%? I would argue that it isn’t, because they have different consumption baskets (and more and more different, as you go higher and higher up the income ladder). If the folks at the top are making more money, but their cost of living is also going up faster, then using the average cost of living increase to deflate both baskets will exaggerate how much better the high-earners are doing than the low-earners. This is potentially a very large effect over this long a time frame. Consider just two categories: food, and shelter. The weights in the CPI tell us that on average, Americans spend about 13% of their income on food and 33% on shelter (these percentages of course shift over time; these are current weights). I suspect that very low earners spend a higher proportion of their budget on food than 13%…probably also more than 33% on shelter, but I suspect that their expenditures are more heavily-weighted towards food than 1:3. But food prices in real terms (deflated by the CPI) are basically unchanged over the last 50 years, while real shelter prices are up about 37%. So, if I am right about the relative expenditure weights of low-earners compared to high-earners, the ‘high-earner’ food/shelter consumption basket has risen by more than the ‘low-earner’ food/shelter consumption basket. Moreover, I think that there are a lot of categories that low-earners essentially consume zero of, or very small amounts of, which have risen in price substantially. Tuition springs to mind. Below I show a chart of CPI-Food, CPI-Shelter, and CPI-College Tuition and Fees, deflated by the general CPI in each case.

The point being that if you look only at incomes, then you are getting an impression from Dalio’s chart – even if my objection #1 and #2 are unimportant – that the lifestyles of the top 40% are improving by lots more than the lifestyles of the bottom 40%. But there is an implicit assumption that these two groups consume the same things, or that the prices of their relative lifestyles are changing similarly. I think that would be a hard argument. What should happen to this chart, then, is that each of these lines should be deflated by a price index appropriate to that group. We would find that the lines, again, would be closer together.

None of these objections means that there isn’t a growing disparity between the haves and the have-nots in our country. My point is simply that the disparity, and moreover the change in the disparity, is almost certainly less than it is generally purported to be with the weakly-assembled statistics we are presented with.


[1] Mr. Mauldin gamely tried to object, but the best he could do was say that capitalists aren’t good at figuring out how to share the wealth. Of course, this isn’t a function of capitalists. The people who decide how to distribute the wealth in capitalism are the consumers, who vote with their dollars. Bill Gates is not uber-rich because he decided to keep hundreds of billions of dollars away from the huddling masses; he is uber-rich because consumers decided to pay hundreds of billions of dollars for what he provided.

Categories: Economics, Politics, Rant, Theory

What if ‘Excess Reserves’ Aren’t Really Excess?

March 4, 2019 2 comments

One intriguing recent suggestion I have heard recently is that the “Excess” reserves that currently populate the balance sheet of the Federal Reserve aren’t really excess after all. Historically, the quantity of reserves was managed so that banks had enough to support lending to the degree which the Fed wanted: when economic activity was too slow, the Fed would add reserves and banks would use these reserves to make loans; when economic activity was too fast, the Fed would pull back on the growth of reserves and so rein in the growth of bank lending. Thus, at least in theory the Open Markets Desk at the New York Fed could manage economic activity by regulating the supply of reserves in the system. Any given bank, if it discovered it had more reserves than it needed, could lend those reserves in the interbank market to a bank that was short. But there was no significant quantity of “excess” reserves, because holding excess reserves cost money (they didn’t pay interest) – if the system as a whole had “too many” reserves, banks tended to lend more and use them up. So, when the Fed wanted to stuff lots of reserves into the system in the aftermath of the financial crisis, and especially wanted the banks to hold the excess rather than lending it, they had to pay banks to do so and so they began to pay interest on reserves. Voila! Excess reserves appeared.

But there is some speculation that things are different now because in 2011, the Basel Committee on Banking Supervision recommended (and the Federal Reserve implemented, with time to comply but fully implemented as of 2015) a rule that all “Systematically Important Financial Institutions” (mainly, really big banks) be required to maintain a Liquidity Coverage Ratio (LCR) at a certain level. The LCR is calculated by dividing a bank’s High Quality Liquid Assets (HQLA) by a number that represents its stress-tested 30-day net outflows. That is, the bank’s liquidity is expressed as a function of the riskiness of its business and the quantity of high-quality assets that it holds against these risks.

In calculating the HQLA, most assets the bank holds receive big discounts. For example, if a bank holds common equities, only half of the value of those equities can be considered in calculating this numerator. But a very few types of assets get full credit: Federal Reserve bank balances and Treasury securities chief among them.[1]

So, since big banks must maintain a certain LCR, and reserves are great HQLA assets, some observers have suggested that this means the Fed can’t really drain all of those excess reserves because they are, effectively, required. They’re not required because they need to be held against lending, but because they need to be held to satisfy the liquidity requirements.

If this is true, then against all my expectations the Fed has, effectively, done what I suggested in Chapter 10, “My Prescription” of What’s Wrong with Money? (Wiley, 2016). I quote an extended section from that book, since it turns out to be potentially spot-on with what might actually be happening (and, after all, it’s my book so I hereby give myself permission to quote a lengthy chunk):

“First, the Federal Reserve should change the reserve requirement for banks. If the mountain will not come to Mohammed, then Mohammed must go to the mountain. In this case, the Fed has the power (and the authority) to, at a stroke, redefine reserves so that all of the current “excess” reserves essentially become “required” reserves, by changing the amount of reserves banks are required to hold against loans. No longer would there be a risk of banks cracking open the “boxes of currency” in their vaults to extend more loans and create more money than is healthy for an economy that seeks noninflationary growth. There would be no chance of a reversion to the mean of the money multiplier, which would be devastating to the inflation picture. And the Open Markets Desk at the Fed would immediately regain power over short-term interest rates, because when they add or subtract reserves in open market operations, banks would care.

“To be sure, this would be awful news for the banks themselves and their stock prices would likely take a hit. It would amount to a forcible deleveraging, and impair potential profitability as a result. But we should recognize that such a deleveraging has already happened, and this policy would merely recognize de jure what has already happened de facto.

“Movements in reserve requirements have historically been very rare, and this is probably why such a solution is not being considered as far as I know. The reserve requirement is considered a “blunt instrument,” and you can imagine how a movement in the requirement could under normal circumstances lead to extreme volatility as the quantity of required reserves suddenly lurched from approximate balance into significant surplus or deficit. But that is not our current problem. Our current problem cries out for a blunt instrument!

“While the Fed is making this adjustment, and as it prepares to press money growth lower, they should work to keep medium-term interest rates low, not raise them, so that money velocity does not abruptly normalize. Interest rates should be normalized slowly, letting velocity rise gradually while money growth is pushed lower simultaneously. This would cause the yield curve to flatten substantially as tighter monetary conditions cause short-term interest rates in the United States to rise.

“Of course, in time the Fed should relinquish control of term rates altogether, and should also allow its balance sheet to shrink naturally. It is possible that, as this happens, reserve requirements could be edged incrementally back to normal as well. But those decisions are years away.”

If, in fact, the implementation of the LCR is serving as a second reserve requirement that is larger than the reserve requirement that is used to compute required and “excess” reserves, then the amount of excess reserves is less than we currently believe it to be. The Fed, in fact, has made some overtures to the market that they may not fully “normalize” the balance sheet specifically because the financial system needs it to continue to supply sufficient reserves. If, in fact, the LCR requirement uses all of the reserves currently considered “excess,” then the Fed is, despite my prior beliefs, actually operating at the margin and decisions to supply more or fewer reserves could directly affect the money supply after all, because the reserve requirement has in effect been raised.

This would be a huge development, and would help ameliorate the worst fears of those of us who wondered how QE could be left un-drained without eventually causing a move to a much higher price level. The problem is that we don’t really have a way to measure how close to the margin the Fed actually is; moreover, since Treasuries are a substitute for reserves in the LCR it isn’t clear that the margin the Fed wants to operate on is itself a bright line. It is more likely a fuzzy zone, which would complicate Fed policy considerably. It actually would make the Fed prone to mistakes in both directions, both over-easing and over-tightening, as opposed to the current situation where they are mostly just chasing inflation around (since when they raise interest rates, money velocity rises and that pushes inflation higher, but raising rates doesn’t also lower money growth since they’re not limiting bank activities by reining in reserves at the margin).

I think this explanation is at least partly correct, although we don’t think the condition is as binding as the more optimistic assessments would have it. The fact that M2 has recently begun to re-accelerate, despite the reduction in the Fed balance sheet, argues that we are not yet “at the margin” even if the margin is closer than we thought it was previously.


[1] The assumption in allowing Treasuries to be used at full value seems to be that in a crisis the value of those securities would go up, not down, so no haircut is required. Of course, that doesn’t always happen, especially if the crisis were to be caused, for example, by a failure of the government to pay interest on Treasuries due to a government shutdown. The more honest reason is that if the Fed were to haircut Treasuries, banks would hold drastically fewer Treasuries and this would be destabilizing – not to mention bad for business on Capitol Hill.

What’s Bad About the Fed Put…and Does Powell Have One?

January 8, 2019 3 comments

Note: Come hear me speak this month at the Taft-Hartley Benefits Summit in Las Vegas January 20-22, 2019. I will be speaking about “Pairing Liability Driven Investing (LDI) and Risk Management Techniques – How to Control Risk.” If you come to the event I’ll buy you a drink. As far as you know.

And now on with our irregularly-scheduled program.


Have we re-set the “Fed put”?

The idea that the Fed is effectively underwriting the level of financial markets is one that originated with Greenspan and which has done enormous damage to markets since the notion first appeared in the late 1990s. Let’s review some history:

The original legislative mandate of the Fed (in 1913) was to “furnish an elastic currency,” and subsequent amendment (most notably in 1977) directed the Federal Open Market Committee to “maintain long run growth of the monetary and credit aggregates commensurate with the economy’s long run potential to increase production, so as to promote effectively the goals of maximum employment, stable prices and moderate long-term interest rates.” By directing that the Federal Reserve focus on monetary and credit aggregates, Congress clearly put the operation of monetary policy a step removed from the unhealthy manipulation of market prices.

The Trading Desk at the Federal Reserve Bank of New York conducts open market operations to make temporary as well as permanent additions to and subtractions from these aggregates by repoing, reversing, purchasing, or selling Treasury bonds, notes, and bills, but the price of these purchases has always been of secondary importance (at best) to the quantity, since the purpose is to make minor adjustments in the aggregates.

This operating procedure changed dramatically in the global financial crisis as the Fed made direct purchase of illiquid securities (notably in the case of the Bear Stearns bankruptcy) as well as intervening in other markets to set the price at a level other than the one the free market would have determined. But many observers forget that the original course change happened in the 1990s, when Alan Greenspan was Chairman of the FOMC. Throughout his tenure, Chairman Greenspan expressed opinions and evinced concern about the level of various markets, notably the stock market, and argued that the Fed’s interest in such matters was reasonable since the “wealth effect” impacted economic growth and inflation indirectly. Although he most-famously questioned whether the market was too high and possibly “irrationally exuberant” in 1996, the Greenspan Fed intervened on several occasions in a manner designed to arrest stock market declines. As a direct result of these interventions, investors became convinced that the Federal Reserve would not allow stock prices to decline significantly, a conviction that became known among investors as the “Greenspan Put.”

As with any interference in the price system, the Greenspan Put caused misallocation of resources as market prices did not truly reflect the price at which a willing buyer and a willing seller would exchange ownership of equity risks, since both buyer and seller assumed that the Federal Reserve was underwriting some of those risks. In my first (not very good) book Maestro, My Ass!, I included this chart illustrating one way to think about the inefficiencies created:

The “S” curve is essentially an efficient frontier of portfolios that offer the best returns for a given level of risk. The “D” curves are the portfolio preference curves; they are convex upwards because investors are risk-averse and require ever-increasing amounts of return to assume an extra quantum of risk. The D curve describes all portfolios where the investor is equally satisfied – all higher curves are of course preferred, because the investor would get a higher return for a given level of risk. Ordinarily, this investor would hold the portfolio at E, which is the highest curve he/she can achieve given his/her preferences. The investor would not hold portfolio Q, because that portfolio has more risk than the investor is willing to take for the level of expected return offered, and he/she can achieve a ‘better’ portfolio (higher curve) at E.

But suppose now that the Fed limits the downside risk of markets by providing a ‘put’ which effectively caps the risk at X. Then, this investor will in fact choose portfolio Q, because portfolio Q offers higher return at a similar risk to portfolio E. So the investor ends up owning more risky securities (or what would be risky securities in the absence of the Fed put) than he/she otherwise would, and fewer less-risky securities. More stocks, and fewer bonds, which raises the equilibrium level of equity prices until, essentially, the curve is flat beyond E because at any increment in return, for the same risk, an investor would slide to the right.

So what happened? The chart below shows a simple measure of expected equity real returns which incorporates mean reversion to long-term historical earnings multiples, compared to TIPS real yields (prior to 1997, we use Enduring Investments’ real yield series, which I write about here). Prior to 1987 (when Greenspan took office, and began to promulgate the idea that the Fed would always ride to the rescue), the median spread between equity expected returns and long-term real yields was about 3.38%. That’s not a bad estimate of the equity risk premium, and is pretty close to what theorists think equities ought to offer over time. Since 1997, however – and here it’s especially important to use median since we’ve had multiple booms and busts – the median is essentially zero. That is, the capital market line averages “flat.”

If this makes investors happy (because they’re on a higher indifference curve), then what’s the harm? Well, this put (a free put struck at “X”) is not costless even though the Fed is providing it for free. If the Fed could provide this without any negative consequences, then by all means they ought to because they can make everyone happier for free. But there is, of course, a cost to manipulating free markets (Socialists, take note). In this case the cost appears in misallocation of resources, as companies can finance themselves with overvalued equity…which leads to booms and busts, and the ultimate bearer of this cost is – as it always is – the citizenry.

In my mind, one of the major benefits that Chairman Powell brought to the Chairmanship of the Federal Reserve was that, since he is not an economist by training, he treated economic projections with healthy and reasonable skepticism rather than with the religious faith and conviction of previous Fed Chairs. I was a big fan of Powell (and I haven’t been a big fan of many Chairpersons) because I thought there was a decent chance that he would take the more reasonable position that the Fed should be as neutral as possible and do as little as possible, since after all it turns out that we collectively suck when it comes to our understanding of how the economy works and we are unlikely to improve in most cases on the free market outcome. When stocks started to show some volatility and begin to reprice late last year, his calculated insouciance was absolutely the right attitude – “what Fed put?” he seemed to be saying. Unfortunately, the cost of letting the market re-adjust is to let it fall a significant amount so that there is again an upward slope between E and Q, and moreover let it stay there.

The jury is out on whether Powell does in fact have a price level in mind, or if he merely has a level of volatility in mind – letting the market re-adjust in a calm and gentle way may be acceptable to him, with his desire to intervene only being triggered by a need to calm things rather than to re-inflate prices. I’m hopeful that is the case, and that on Friday he was just trying to slow the descent but not to arrest it. My concern is that while Powell is not an economist, he did have a long career in investment banking, private equity, and venture capital. That might mean that he respects the importance of free markets, but it also might mean that he tends to exaggerate the importance of high valuations. Again, I’m hopeful, and optimistic, on this point. But that translates to being less optimistic on equity prices, until something like the historical risk premium has been restored.

Spinning Economic Stories

January 4, 2019 5 comments

As economists[1] we do two sorts of things. We do quantitative work, and we tell stories.

One of the problems with economics is that we aren’t particularly regimented about how we convert data into stories and about how we look at stories to decide how to interrogate the data. So what tends to happen is that we have a phenomenon and then we look at what story we like and decide if that’s a reasonable way to explain the data…without asking if there isn’t a more reasonable way to explain the data, or at least another way that’s equally consistent with the data. I’m not saying that everyone does this, just that it’s disturbingly common especially among people being paid to be storytellers and for whom a good story is really important.

So for example, there is a well -known phenomenon that inflation tends to accelerate after the Fed begins raising interest rates.[2] Purporting to explain this phenomenon, here is a popular story that the Fed is just really smart, so they’re ahead of inflation, and when they seeing it moving up just a little bit they can jump on it real quick and get ahead of it and so inflation goes up…but the apparent causality is there because we just knew it was going to go up and acted before the observation of the higher inflation happened. This is basically Keynesian theory combined with “brilliant person” theory.

There is another theory that is consistent with this, of course: monetarism, which explains that increasing interest rates actually causes inflation to move higher, by causing velocity to increase. But, because this isn’t the popular story, this doesn’t get matched up to the data very frequently. In my mind it’s a better theory, because it doesn’t require us to believe that the Fed is super brilliant to make it work. (And, not to get snarky, but the countervailing evidence versus Fed staff economist genius is pretty mountainous). Of course, economists – and the Fed economists in particular – like theories that make them look like geniuses, so they prefer the prior explanation.

But again, as economists we don’t have a good and rigorous way to say that one way is the ‘preferred’ story or to look at other stories that are consistent with our data. We tend to look at what part of the data supports our story – in other words, confirmation bias.

Why this is relevant now is that the Fed is in fact tightening and inflation is in fact heading higher, and the story being pushed by the Fed and some economists is “good thing the Fed is tightening, because it looks like inflation was going up!” The story on the other hand that I have been telling for quite some time (and which I write about in my book) is that it’s partly because the Fed is tightening and interest rates are going up that that inflation is rising, in a feedback loop that is missed in our popular stories. The important part is the next chapter in the story. In the “Fed is getting ahead of it” story, inflation comes down and the Fed is able to stop tightening, achieving a soft landing. In the “rate increase is causing velocity to rise and inflation to rise” story, the Fed keeps chasing the dog which is only running because the Fed is chasing it.

There is another alternative, which really excites the stock market as evidenced by today’s massive – although disturbingly low-volume – rally. That story is that the Fed is going to become more “data dependent” (Chairman Powell suggested something along these lines today), which is great because the Fed has already won on inflation and growth is still okay. So the Fed can stop the autopilot rate hikes. This story unfortunately does require a little suspension of disbelief. For one thing, today’s strong Employment report (Payrolls 370k, including revisions, compared to 184k expectations) is unfortunately a December figure which means it has huge error bars. Moreover, the Unemployment Rate rose to 3.9% from 3.7%, and while a higher Unemployment Rate doesn’t mean the economy is definitely slowing (it could just be that more people are looking for jobs because the job market is so robust – another fun story), it is certainly more consistent with the notion that the economy is slowing at the margin. The fact that the Unemployment Rate went up, while Hourly Earnings rose more than expected and Jobs rose more than expected, should make you suspect that year-end quirkiness might have something to do with the figures. For the decades I’ve watched economic data, I always advise ignoring the January and February Employment Reports since the December/January changes in payroll are so large that the noise swamps the signal. But professional storytellers aren’t really content to say “this doesn’t really mean anything,” even if that’s the quantitative reality. They get paid to spin yarns, so spin yarns they do.

Yeah, about those wages: I’m not really sure why economists were expecting hourly earnings to decelerate this month. All of the anecdotal data, along with other wage measures, are suggesting that wages are rising apace (see chart, source Bloomberg, showing the Atlanta Fed Wage Tracker vs AHE). Not really a surprise, even given its compositional challenges, that AHE is also rising.

The thing about all of these stories is that while they can’t change the actual reality, they can change how reality is priced. This is one of the reasons that we get bubbles. The stories are so powerful that trading against them, with a ‘value’ mindset for example, is quixotic. Ultimately, in the long run, the value of the equity market is limited by fundamentals. But in the short run, it is virtually unlimited because of valuation multiples (price as a speculative multiple of fundamental earnings, e.g.) and those valuation multiples are driven by stories. And that’s a big reason that bullish stories are so popular.

But consider this bearish footnote on today’s 3.4% S&P rally: volume in the S&P constituents today was lower than the volume was on December 26! To be fair, the volume yesterday, when the S&P declined 2.5%, was even a bit lower than today’s volume. It’s typical thin and whippy first-week-of-the-year trading. Let’s see what next week brings.


[1] People occasionally ask me why I didn’t go on for my MA or PhD in Economics. I reply that it’s because I learned my Intermediate Microeconomics very well: I stopped going for a higher degree when the marginal costs outweighed the marginal benefits. When you look at it that way, it makes you wonder whether the PhD economists aren’t just the bad students who didn’t absorb that lesson.

[2] It’s referred to as the “price puzzle”; see Martin Eichenbaum, “Interpreting Macroeconomic Time Series Facts: The Effects of Monetary Policy: Comments.” European Economic Review, June 1992. And Michael Hanson, “The ‘Price Puzzle’ Reconsidered,” Journal of Monetary Economics, October 2004.

Alternative Risk Premia in Inflation Markets

July 25, 2018 1 comment

I’m going to wade into the question of ‘alternative risk premia’ today, and discuss how this applies to markets where I ply my trade.

When people talk about ‘alternative risk premia,’ they mean one of two things. They’re sort of the same thing, but the former meaning is more precise.

  1. A security’s return consists of market beta (whatever that means – it is a little more complex than it sounds) and ‘alpha’, which is the return not explained by the market beta. If rx is the security return and rm is the market return, classically alpha isThe problem is that most of that ‘alpha’ isn’t really alpha but results from model under-specification. For example, thanks to Fama and French we have known for a long time that small cap stocks tend to add “extra” return that is not explained by their betas. But that isn’t alpha – it is a beta exposure to another factor that wasn’t in the original model. Ergo, if “SMB” is how we designate the performance of small stocks minus big stocks, a better model isWell, obviously it doesn’t stop there. But the ‘alpha’ that you find for your strategy/investments depends critically on what model you’re using and which factors – aka “alternative risk premia” – you’re including. At some level, we don’t really know whether alpha really exists, or whether systematic alpha just means that we haven’t identified all of the factors. But these days it is de rigeur to say “let’s pay very little in fees for market beta; pay small fees for easy-to-access risk premia that we proactively decide to add to the portfolio (overweighting value stocks, for example), pay higher fees for harder-to-access risk premia that we want, and pay a lot in fees for true alpha…but we don’t really think that exists.” Of course, in other people’s mouths (mostly marketers) “alternative risk premia that you should add to your portfolio” just means…
  2. Whatever secret sauce we’re peddling, which provides returns you can’t get elsewhere.

So there’s nothing really mysterious about the search for ‘alternative risk premia’, and they’re not at all new. Yesteryear’s search for alpha is the same as today’s search for ‘alternative risk premia’, but the manager who wants to earn a high fee needs to explain why he can add actual alpha over not just the market beta, but the explainable ‘alternative risk premia’. If your long-short equity fund is basically long small cap stocks and short a beta-weighted amount of large-cap stocks, you’re probably not going to get paid much.

For many years, I’ve been using the following schematic to explain why certain sources of alpha are more or less valuable than others. The question comes down to the source of alpha, after you have stripped out the explainable ‘alternative risk premia’.

As an investor, you want to figure out where this manager’s skill is coming from: is it from theoretical errors, such as when some guys in Chicago discovered that the bond futures contract price did not incorporate the value of delivery options that accrued to the contract short, and harvested alpha for the better part of two decades before that opportunity closed? Or is it because Joe the trader is really a great trader and just has the market’s number? You want more of the former, which have high information ratios, are very persistent…but don’t come around that much. You shouldn’t be very confident in the latter, which seem to be all over the place but don’t tend to last very long and are really hard to prove. (I’ve been waiting for a long time to see the approach to fees suggested here in a 2008 Financial Analysts’ Journal article implemented.)

I care about this distinction because in the markets I traffic in, there are significant dislocations and some big honking theoretical errors that appear from time to time. I should hasten to say that in what follows, I will mention some results for strategies that we have designed at Enduring Intellectual Properties and/or manage via Enduring Investments, but this article should not be construed as an offer to sell any security or fund nor a solicitation of an offer to buy any security or fund.

  • Let’s start with something very simple. Here is a chart of the first-derivative of the CPI swaps curve – that is, the one-year inflation swap, x-years forward (so a 1y, 1y forward; a 1y, 2y forward; a 1y, 3y forward, and so on). In developed markets like LIBOR, not only is the curve itself smooth but the forwards derived from that curve are also smooth. But this is not the case with CPI swaps.[1]

  • I’ve also documented in this column from time to time the fact that inflation markets exaggerate the importance of near-term carry, so that big rallies in energy prices not only affect near-term breakevens and inflation swaps but also long-dated breakevens and inflation swaps, even though energy prices are largely mean-reverting.
  • We’ve in the past (although not in this column) identified times when the implied volatility of core inflation was actually larger than the implied volatility of nominal rates…which outcome, while possible, is pretty unlikely.
  • Back in 2009, we spoke to investors about the fact that corporate inflation bonds (which are structured very differently than TIPS and so are hard to analyze) were so cheap that for a while you could assemble a portfolio of these bonds, hedge out the credit, and still realize a CPI+5% yield at time when similar-maturity TIPS were yielding CPI+1%.
  • One of my favorite arbs available to retail investors was in 2012, when I-series savings bonds from the US Treasury sported yields nearly 2% above what was available to institutional investors in TIPS.

But aside from one-off trades, there are also systematic strategies. If a systematic strategy can be designed that produces excess returns both in- and out- of sample, it is at least worth asking whether there’s ‘alpha’ (or undiscovered/unexploited ‘alternative risk premia’) here. All three of the strategies below use only liquid markets – the first one, only commodity futures; the second one, only global sovereign inflation bonds; and the third one, only US TIPS and US nominal Treasuries. The first two are ‘long only’ strategies that systematically rebalance monthly and choose from the same securities that appear in the benchmark comparison. (Beyond that, this public post obviously needs to keep methods undisclosed!). And also, please note that past results are no indication of future returns! I am trying to make the general point that there are interesting risk factors/alphas here, and not the specific point about these strategies per se.

  • Our Enduring Dynamic Commodity Index is illustrated below. It’s more volatile, but not lots more volatile: 17.3% standard deviation compared to 16.1% for the Bloomberg Commodity Index.

That’s the most-impressive looking chart, but that’s because it represents commodity markets that have lots of volatility and, therefore, offer lots of opportunities.

  • Our Global Inflation Bond strategy is unlevered and uses only the bonds that are included in the Bloomberg-Barclays Global ILB index. It limits the allowable overweights on smaller markets so that it isn’t a “small market” effect that we are capturing here. According to the theory that drives the model, a significant part of any country’s domestic inflation is sourced globally and therefore not all of the price behavior of any given market is relevant to the cross-border decision. And that’s all I’m going to say about that.

  • Finally, here is a simple strategy that is derived from a very simple model of the relationship between real and nominal Treasuries to conclude whether TIPS are appropriately priced. The performance is not outlandish, and there’s a 20% decline in the data, but there’s also only one strategy highlighted here – and it beats the HFR Global Hedge Fund Index.

I come not to bury other strategies but to praise them. There are good strategies in various markets that deliver ‘alternative risk premia’ in the first sense enumerated above, and it is a good thing that investors are extending their understanding beyond conventional beta as they assemble portfolios. I believe that there are also strategies in various markets which deliver ‘alternative risk premia’ that are harder to access because they require rarer expertise. Finally, I believe that there are strategies – but these are very rare, and getting rarer – which deliver true alpha that derives from theoretical errors or systematic imbalances. I think that as a source of a relatively unexploited ‘alternative risk premium’ and a potential source of unique alphas, the inflation and commodity markets still contain quite a few useful nuggets.


[1] I am not necessarily claiming that this can be exploited easily right now, but the curve has had such imperfections for more than a decade – and sometimes, it’s exploitable.

Categories: Good One, Investing, Theory, TIPS Tags:
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